Apparatus, method and computer program product for delay selection in a spread-spectrum receiver
Abstract
A method of recovering a signal from a composite signal, including signals from one or more sources, the method comprising: - determining (1010) the channel and correlation characteristics for the composite signal; - determine (1020) the respective combination weights for an information from the composite signal for the respective of a plurality of candidate delays based on the determined channel and correlation characteristics; characterized in that the method further comprises - selecting (1030) a first delay from the plurality of candidate delays for inclusion in a group of delays; - generate an estimate of signal and noise content for the respective of a plurality of certain delays from a weighting associated with the first delay; - select one or more of the respective plurality of second delays for inclusion in the group of delays based on the estimation of signal content and generated noise; and - processing (1040) an information from the composite signal for the delays selected according to a spreading code to generate a symbol estimate.

Term
Term ended
Projected expiry passed 4 October 2025, 1 year ago.
- Priority
- Filed
- Published
- Projected expiry
- Today
16 claims: 3 independent, 13 dependent
- 1ES 2 425 225 T3 reivindicaciones 1. Un método de recuperación de una señal a partir de una señal compuesta, incluyendo señales de una o más fuentes, el método que comprende:• determinar (1010) las características de canal y de correlación para la señal compuesta;• determinar (1020) las ponderaciones de combinación respectivas para una información a partir de la señal compuesta para los respectivos de una pluralidad de retardos candidatos en base a las características de canal y de correlación determinadas;caracterizado porque el método además comprende • seleccionar (1030) un primer retardo a partir de la pluralidad de retardos candidatos para inclusión en un grupo de retardos;• generar una estimación de contenido de señal y de ruido para los respectivos de una pluralidad de segundos retardos a partir de una ponderación asociada con el primer retardo;• seleccionar uno o más de los respectivos de la pluralidad de segundos retardos para inclusión en el grupo de retardos en base a la estimación de contenido de señal y de ruido generada;y • procesar (1040) una información a partir de la señal compuesta para los retardos seleccionados según un código de ensanchado para generar una estimación de símbolo.
- 2Un método según la reivindicación 1, en donde generar una estimación de contenido de señal y de ruido para un segundo retardo a partir de una ponderación asociada con el primer retardo comprende:• determinar una correlación entre una información de señal compuesta para el primer retardo y una información de señal compuesta para el segundo retardo;y • generar la estimación de contenido de señal y de ruido para el segundo retardo a partir de la correlación y la ponderación asociadas con el primer retardo.
- 3Un método según la reivindicación 1:• en donde generar una estimación de contenido de señal y de ruido para un segundo retardo a partir de una ponderación asociada con el primer retardo comprende generar estimaciones respectivas de contenido de señal y de ruido para los respectivos de la pluralidad de segundos retardos a partir de la ponderación asociada con el primer retardo;y • en donde seleccionar el uno o más de los respectivos de la pluralidad de segundos retardos para inclusión en el grupo de retardos en base a la estimación de contenido de señal y de ruido generada comprende seleccionar de entre la pluralidad de segundos retardos en base a las estimaciones de contenidos de señal y de ruido.
- 4Un método según la reivindicación 3, en donde seleccionar de entre la pluralidad de segundos retardos en base a las estimaciones de contenido de señal y de ruido comprende seleccionar segundos retardos cuyas estimaciones de contenido de señal y de ruido asociadas indican una mejora más grande de la relación señal a ruido.
- 5Un método según la reivindicación 3:• en donde seleccionar de entre la pluralidad de segundos retardos en base a las estimaciones de contenido de señal y de ruido comprende seleccionar uno primero de los segundos retardos;• en donde determinar las ponderaciones de combinación respectivas para una información a partir de la señal compuesta para los respectivos de una pluralidad de retardos candidatos en base a las características de canal y de correlación determinadas comprende determinar nuevas ponderaciones de combinación respectivas para los respectivos del grupo seleccionado de retardos incluyendo el primero seleccionado de los segundos retardos;• en donde generar las estimaciones de contenido de señal y de ruido respectivas para los respectivos de la pluralidad de segundos retardos a partir de la ponderación asociada con el primer retardo comprende generar nuevas estimaciones de contenido de señal y de ruido para los respectivos de la pluralidad de segundos retardos aún no seleccionados;y • en donde seleccionar de entre la pluralidad de segundos retardos en base a las estimaciones de contenido de señal y de ruido comprende seleccionar uno segundo de los segundos retardos en base a las nuevas estimaciones de contenido de señal y de ruido.
- 6Un método según la reivindicación 5, en donde seleccionar uno segundo de los segundos retardos en base a las nuevas estimaciones de contenido de señal y de ruido comprende sustituir el segundo de los segundos retardos para uno seleccionado previamente del grupo seleccionado de retardos en base a una comparación de las estimaciones de contenido de señal y de ruido. ES 2 425 225 T3
- 7Un método según la reivindicación 3, en donde seleccionar de entre la pluralidad de segundos retardos en base a las estimaciones de contenido de señal y de ruido comprende:• generar una estimación de contenido de señal y de ruido agregada para un conjunto de los segundos retardos;y • determinar si seleccionar el conjunto de segundos retardos para inclusión en el grupo de retardos seleccionados en base a la estimación de contenido de señal y de ruido agregada.
- 8Un método según la reivindicación 1, en donde procesar la información a partir de la señal compuesta para los retardos seleccionados según un código de ensanchado para generar una estimación de símbolo comprende:• generar las correlaciones respectivas de la señal compuesta con el código de ensanchado para los respectivos de los retardos seleccionados;y • combinar las correlaciones generadas para generar la estimación de símbolo.
- 9Un método según la reivindicación 1, en donde procesar la información a partir de la señal compuesta para los retardos seleccionados según un código de ensanchado para generar una estimación de símbolo comprende:• filtrar la señal compuesta usando un filtro que tiene derivadores de filtro correspondientes a los respectivos de los retardos seleccionados;y • correlacionar las señales de comunicaciones de espectro ensanchado filtradas con el código ensanchado para generar la estimación de símbolo.
- 10Un método según la reivindicación 1, en donde determinar las características de canal y de correlación para la señal compuesta comprende determinar la característica de correlación paramétricamente y no paramétricamente.
- 11Un método según la reivindicación 1, en donde determinar las características de canal y de correlación para la señal compuesta comprende determinar la característica de correlación a partir de las correlaciones de la señal compuesta en la pluralidad de retardos candidatos.
- 12Un receptor de comunicaciones de espectro ensanchado (600) que comprende:• un procesador radio (650) configurado para recibir una señal radio que incluye señales de una o más fuentes y producir una señal en banda base compuesta que incluye señales de una o más fuentes;y • un procesador en banda base configurado para determinar (640) las características de canal y de correlación para la señal compuesta, determinar (630) las ponderaciones de combinación respectivas para información a partir de la señal compuesta para los respectivos de una pluralidad de retardos candidatos en base a las características de canal y de correlación determinadas, caracterizado porque el procesador en banda base está configurado además: • para seleccionar (620) un primer retardo a partir de la pluralidad de retardos candidatos para inclusión en un grupo de retardos, para generar una estimación de contenido de señal y de ruido para los respectivos de una pluralidad de segundos retardos a partir de una ponderación asociada con el primer retardo, seleccionar (620) uno o más de los respectivos de la pluralidad de segundos retardos para inclusión en el grupo de retardos en base a la estimación generada de contenido de señal y de ruido, y procesar (610) una información a partir de la señal compuesta para los retardos seleccionados según un código de ensanchado para generar una estimación de símbolo.
- 13Un receptor según la reivindicación 12, en donde el procesador en banda base es operativo para generar una estimación de contenido de señal y de ruido agregada para un conjunto de los segundos retardos, y determinar si seleccionar el conjunto de los segundos retardos para inclusión en el grupo de retardos seleccionados en base a la estimación de contenido de señal y de ruido agregada.
- 14Un receptor según la reivindicación 12, en donde el procesador en banda base es operativo para generar correlaciones respectivas de la señal compuesta con el código de ensanchado para los respectivos de los retardos seleccionados, y combinar las correlaciones generadas para generar la estimación de símbolo.
- 15Un receptor según la reivindicación 12, en donde el procesador en banda base es operativo para filtrar la señal compuesta usando un filtro que tiene derivadores de filtro que corresponden a los respectivos de los retardos seleccionados y correlacionar las señales de comunicaciones de espectro ensanchado filtradas con el código de ensanchado para generar la estimación de símbolo.
- 16Un producto de programa informático para recuperar una señal a partir de una señal compuesta que incluye ES 2 425 225 T3 señales de una o más fuentes, el producto de programa informático que comprende un código de programa informático integrado en un medio de almacenamiento legible por ordenador, el código de programa informático configurado para realizar el método según cualquiera de las reivindicaciones 1 a 11.
Independent claims16
139 paragraphs in 10 sections, as filed
ES 2 425 225 T3
DESCRIPTION
Apparatus, methods and software products for delay selection in a spread spectrum receiver
BACKGROUND OF THE INVENTION
The present invention relates to radio communications, and more specifically, to computer program apparatus, methods, and products for processing spread spectrum communications signals.
Spread spectrum signal transmission techniques are widely used in communication systems, such as code division multiple access (CDMA) cellular telephone networks. With reference to FIGURE 1, an information symbol is typically modulated by a spreading sequence prior to transmission from a transmitting station 110 such that the symbol is represented by a number of segments in the transmitted signal. At receiver 120, the received signal is de-spread using a de-spread code, which is typically the conjugate of the spread code. Receiver 120 includes a radio processor 122 that performs down-conversion, filtering, and / or other operations to produce a baseband signal that is provided to a baseband processor 124. Baseband processor 124 de-spreads the baseband signal to produce symbol estimates that are provided to an additional processor 126, which can perform additional signal processing operations, such as error correction decoding.
In coherent direct sequence CDMA (DS-CDMA) systems, coherent RAKE reception is commonly used. This type of receiver de-spreads the received signal by correlating the sequence of segments to produce de-spread values that are weightedly combined according to the estimated channel coefficients. Weighting can eliminate channel phase rotation and adjust de-spread values to provide "soft" values that are indicative of transmitted symbols.
Multipath propagation of the transmitted signal can lead to time dispersion, which causes multiple resolvable echoes of the transmitted signal to reach the receiver. In a conventional RAKE receiver, the correlators are typically aligned with selected echoes of the desired signal. Each correlator produces de-spread values that are weightedly combined as described above. Although a RAKE receiver can be effective in certain circumstances, self and multi-user interference can degrade performance causing loss of orthogonality between defined spreading sequence channels.
A "generalized" RAKE receiver (G-RAKE) has been proposed to provide improved performance in such interference environments. A conventional G-RAKE receiver typically uses combination weights that are a function of the channel coefficients and a noise covariance that includes information regarding the interfering signals. These weights w can be expressed as:
<img file="ES2425225T3_D0001.tif" />
where R is a noise covariance matrix and c is a channel coefficient vector.
A typical baseband processor for a G-RAKE receiver is illustrated in FIGURE 2. The segment samples are provided to a branch placement unit 230, which determines where to place the branches (by selecting delays for one or more antennas) using a correlation unit 210. The correlation unit 210 de-spreads one or more traffic channels and produces de-spread values of traffic. The selected paths are also provided to a weighting computer 240, which calculates the combination weights that are used to combine the de-spread values in a combiner 220 to produce smooth values.
Similar functionality can be provided using a segment equalizer structure, as shown in FIGURE 3. In such a structure, segment samples are provided to a shunt placement unit 330, which determines where to place the filter shunts ( that is, what delays for one or more antennas) for a Finite Impulse Response (FIR) filter 310. The selected shunt locations are also provided to a weighting calculator 340 which calculates the filter coefficients (or weights) for filter 310. Filter 310 filters the segment samples to produce a signal that is de-spread by a correlator 320 to produce symbol estimates.
A conventional weighting computer for a G-RAKE receiver is illustrated in FIGURE 4. Signal samples are provided to a correlation unit 410 that de-spreads symbols from a pilot or traffic channel to produce initial de-spread values. The symbol modulation is removed from these values by a modulation remover 420, and the resulting values are provided to a channel scanner 430 which generates
ES 2 425 225 T3 channel estimates. The de-spread values and channel estimates are provided to a noise covariance estimator 450, which produces an estimate of the noise covariance of the set of delays in use. The channel estimates and the noise covariance estimate are provided to a weighting calculator 440, which computes the combination weights (filter coefficients) thereof.
A G-RAKE receiver differs from a traditional RAKE receiver in that it considers delays in addition to those corresponding to echoes of the desired signal. These other delays are typically chosen to provide information about interference so that the receiver can suppress the interference.
In a practical RAKE receiver (traditional RAKE or G-RAKE), hardware and / or software constraints typically limit the number of "branches" that can be used at any one time. In a traditional RAKE receiver, these branches are typically chosen such that a maximum amount of the desired signal energy is collected. In a G-RAKE receiver, however, the branch selection criteria can also collect information from the interfering signal so that a desired amount of interference suppression can be achieved.
A variety of strategies have been proposed to select branches for RAKE receptors. US Patent No. 5,572,552 to Dent et al. describes a process by which branches are placed according to a signal-to-noise ratio (SNR) metric that is calculated as a function of channel coefficients, power levels, and optionally the spreading code. US Pat. Bottomley No. 6,363,104 describes the estimation of the SNR for different combinations of branch positions as a function of estimates of the channel and estimates of the impairment correlation matrix for each candidate combination, and the selection of a combination of branches that maximizes SNR. US Patent No. 6,683,924 to Ottosson et al. describes a process of selecting branches based on time differentials and relative signal strengths of signal paths. “Low complexity implementation of a downlink CDMA generalized RAKE receiver,” and “On the performance of a practical downlink CDMA generalized RAKE receiver,” by Kutz et al., Actas de Conf. Tecnolog. Veh. of the IEEE, Vancouver, Canada (24-28 September 2002), describe other screening techniques.
US Patent Application No. 2001/0028677 shows methods of recovering information encoded in a spread spectrum signal transmitted according to a spread sequence. A spread spectrum signal is correlated with a spread sequence to produce a plurality of time shift correlations. A subset of the plurality of time shift correlations can then be selected, and the corresponding traffic correlations can then be combined using a weighted combination to estimate the information encoded in the transmitted spread spectrum signal.
COMPENDIUM OF THE INVENTION
The present invention relates to a method according to independent claim 1 and a spread spectrum communications receiver according to independent claim 12. Advantageous embodiments are defined in the dependent claims.
According to some embodiments of the present invention, methods are provided for recovering a signal from a composite signal that includes signals from one or more sources. Channel and correlation characteristics are determined for the composite signal. The respective combination weights for composite signal information are determined for the respective of a plurality of candidate delays based on the determined channel and correlation characteristics. A group of delays, eg, RAKE correlator delays or segment equalizer filter derivatives, is selected from the plurality of candidate delays based on the determined weights. The composite signal information for the selected delays is processed in accordance with a spreading code to generate a symbol estimate.
A time domain channel response and quantity correlation can be determined and the respective weights determined from the time domain channel response and quantity correlation. The quantity correlation can be a noise covariance. The selected group of delays may include a group of delays, for example correlator delays or segment equalizer filter derivatives, which have the highest associated weights.
A frequency domain approach can be used to determine weights for correlator delays and / or segment equalizer filter derivatives. A weighted frequency response is determined that includes noise information, and the respective weights are determined from the weighted frequency response, for example, by converting the effective channel response to the time domain to determine the coefficients of a channel model. effective in the corresponding time domain. Delays with the highest coefficients can be selected.
According to embodiments of the present invention, delays can be incrementally selected for inclusion in a group of delays. A first delay is selected from the group of delays, for example, using the techniques described above or some other selection technique. An estimate of signal content and
Noise is estimated for the respective of a plurality of second delays from a weighting associated with the first delay. One or more of the plurality of second delays is selected for the group of delays based on the generated noise and signal content estimate. A correlation between the composite signal information for the first delay and the composite signal information for the second delay can be determined, and the signal content and noise estimate for the second delay can be determined from the correlation and weighting associated with the first delay. An estimate of signal and noise content can be generated without inverting a noise covariance matrix.
In some embodiments of the present invention, the respective noise and signal content estimates for the respective of the plurality of second delays can be generated from the weighting associated with the first delay. Selecting a second delay for the group of delays based on the generated noise and signal content estimate may include selecting from the plurality of second delays based on the noise and signal content estimates. Such a process can occur iteratively, for example, a first of the second delays can be selected, followed by determining new respective weights for the respective of the selected group of delays including the first selected of the second delays, generating new estimates of signal content and noise for the respective of the plurality of second delays not yet selected, and selecting one second of the second delays based on the new noise and signal content estimates. Selecting a new candidate delay may include replacing a previously selected one from the selected group of delays based on a comparison of noise and signal content estimates.
In still further aspects of the present invention, delays, for example RAKE correlator delays and / or segment equalizer filter derivatives, can be evaluated in an aggregate manner, eg, as "super branches". An aggregate noise and signal content estimate is generated for a set of delays. The set of delays is evaluated for inclusion in the group of selected delays based on the aggregate noise and signal content estimate.
In still further embodiments of the present invention, a signal is recovered from a composite signal. Channel and correlation characteristics are determined for the composite signal. The respective combination weights for composite signal information are determined for the respective of a plurality of candidate delays based on the determined channel and correlation characteristics. A first delay is selected for inclusion in a delay group. An estimate of signal and noise content is generated for a second delay from a weighting associated with the first delay. The second delay is selected for inclusion in the delay group based on the generated noise and signal content estimate. The composite signal information for the selected delays is processed in accordance with a spreading code to generate a symbol estimate.
In further embodiments of the present invention, a spread spectrum communications receiver includes a radio processor configured to receive a radio signal that includes signals from a plurality of sources and to produce a composite baseband signal that includes signals from a plurality of sources. The receiver further includes a baseband processor configured to determine the channel and correlation characteristics for the composite signal, determine the respective weights for information from the composite signal for the respective of the plurality of candidate delays based on the characteristics. of determined channel and correlation, select a group of delays from the plurality of candidate delays based on the determined weights, and processing information from the composite signal for selected delays in accordance with a spreading code to generate a symbol estimate.
According to further embodiments of the present invention, a computer program product includes computer program code that includes code configured to perform the method.
BRIEF DESCRIPTION OF THE DRAWINGS
FIGURE 1 is a block diagram illustrating a conventional spread spectrum communication system.
FIGURE 2 is a block diagram illustrating a conventional baseband processor with a generalized RAKE structure.
FIGURE 3 is a block diagram illustrating a conventional baseband processor with a segment equalizer structure.
FIGURE 4 is a block diagram illustrating a weighting computer for a generalized RAKE receiver.
FIGURE 5 is a block diagram illustrating a signal processing apparatus according to some embodiments of the present invention.
FIGURE 6 is a block diagram illustrating a radio receiver in accordance with additional embodiments of the present invention.
FIGURE 7 is a block diagram illustrating a signal processing apparatus with a generalized RAKE structure according to further embodiments of the present invention.
ES 2 425 225 T3
FIGURE 8 is a block diagram illustrating a signal processing apparatus with a segment equalizer structure according to further embodiments of the present invention.
FIGURE 9 is a block diagram illustrating a signal processing apparatus with a probe branch unit according to further embodiments of the present invention.
FIGURES 10, 13 through 16 are flowcharts illustrating various filter bypass and correlator branch selection operations in accordance with various embodiments of the present invention.
FIGURES 11 through 12 are flowcharts illustrating various correlator branch and filter tappet selection operations,
FIGURE 17 is a block diagram illustrating a system model for a spread spectrum communication system.
FIGURE 18 is a flow chart illustrating correlator branch and filter tappet selection operations.
FIGURE 19 is a block diagram illustrating a nonparametric noise covariance estimator. FIGURE 20 is a block diagram illustrating a parametric noise covariance estimator.
DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS
The present invention will now be more fully described hereinafter with reference to the accompanying drawings, in which embodiments of the invention are shown. However, this invention should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this description will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to the same elements everywhere.
It will also be understood that, as used herein, the terms "comprising", "comprises", "includes" and "including" are open-ended, that is, they refer to one or more elements, steps, and / or functions indicated without excluding one or more elements, steps and / or functions not indicated. The term "and / or" as used herein will also be understood to refer to and encompass any and all possible combinations of one or more of the associated enumerated subjects. It will further be understood that when transfer, communication or other interaction is described as occurring "between" elements, such transfer, communication or other interaction may be unidirectional and / or bidirectional.
The present invention is described below with reference to block diagrams and / or operational illustrations of methods, apparatus, and computer program products in accordance with embodiments of the invention. It will be understood that each block in the block diagrams and / or operational illustrations, and combinations of blocks in the block diagrams and / or operational illustrations, can be implemented by analog and / or digital hardware and / or computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, ASIC, and / or other programmable data processing apparatus, so that the instructions, which run through the computer's processor and / or other programmable data processing apparatus, create means to implement the functions / actions specified in the block diagrams and / or operational illustrations. In some alternative implementations, the functions / actions outlined in the figures may occur out of the order outlined in the block diagrams and / or operational illustrations. For example, two operations shown to occur in succession may in fact be executed substantially concurrently or the operations may sometimes be executed in the reverse order, depending on the functionality / actions involved.
According to some embodiments of the present invention, the electronic apparatus may include a radio receiver configured to provide the operations described herein. Such a receiver can be included in any of a number of types of devices, including, but not limited to: cellular telephone sets and other wireless terminals, cellular base stations and other types of radio network nodes, and wired receiver devices. The computer program code for carrying out the operations of the present invention may be written in an object-oriented programming language, a procedural programming language, or lower-level code, such as assembly language and / or micro code. The program code may run entirely on a single processor and / or across multiple processors, as a standalone software package or as part of another software package.
According to various embodiments of the invention, the determination of delays, for example, signal paths such as the RAKE correlator branches or equalizer filter derivatives, can be achieved by determining the candidate delay weights from the channel and correlator characteristics. for a composite signal. In some exemplary embodiments, a maximum weighting criterion may be used to select correlator delays and / or equalizer filter shunts. In other exemplary embodiments, a signal-to-noise ratio metric derived from the weights can be used to identify desirable delays or shunts. In further embodiments, a channel frequency response can be used to calculate the weights, which can be selected by a maximum weight or other criteria.
FIGURE 5 illustrates a signal processing apparatus 500 according to some embodiments herein.
ES 2 425 225 T3 invention. Apparatus 500 includes a symbol estimator 510, for example, a combination of a correlation unit and combiner as used in a generalized RAKE receiver architecture or a combination of a FIR filter and a correlator as used in a segment equalizer. . Symbol estimator 510 processes a composite signal according to a spreading code using delays, eg, correlator delays or filter derivatives, selected from a plurality of candidate delays by delay selector 520. Delay selector 520 selects delays in response to combining weights generated by a weighting determiner 530. Combination weights 530 are generated in response to channel and correlation characteristics determined by a channel and correlation determiner 540.
As described in detail below, apparatus and operations along the lines described with reference to apparatus 500 can be implemented in a number of different ways in accordance with various embodiments of the present invention. For example, according to various embodiments of the invention, the selection of delays, for example correlator branch delays, equalizer filter shunts, and / or signal sources (for example, different antennas), occurs based on a maximum weighting criterion. . In other exemplary embodiments, a signal-to-noise ratio metric derived from such weights can be used to identify desirable correlator (branch) or shunt delays. In further embodiments, a channel frequency response can be used to calculate weights, which can be selected by a maximum weight or other criteria.
It can be appreciated that apparatus and methods according to various embodiments of the invention can be generally implemented using analog and / or digital electronic circuits. For example, function blocks 510-540 can be implemented using program code that runs on a data processing device, such as a microprocessor or digital signal processor (DSP), or on data processing circuitry included in a special purpose electronic device, such as a communications ASIC. The present invention can also be integrated as computer code configured such that, when executed on a data processing device, it provides the operations described above.
FIGURE 6 illustrates a receiver 600 that includes signal processing apparatus along the lines shown in FIGURE 5. Radio signals, which may include information from multiple transmission sources, are received by an antenna 670 and provided to a radio processor 650, which performs filtering, downconversion, and other processes that produce a composite baseband signal. The baseband signal is provided to a baseband processor that includes a symbol estimator 610, a delay selector 620, a channel and correlation determiner 640, and a weighting determiner 630, which can function in the same way as the corresponding elements described below with reference to FIGURE 5. The symbol estimates produced by the symbol estimator 610 are provided to an additional processor 660, which can perform other signal processing functions, such as error correction decoding.
FIGURE 7 illustrates a signal processing apparatus 700 according to additional embodiments of the present invention. Apparatus 700 includes a symbol estimator 710 that processes a composite signal to generate a symbol estimate. Symbol estimator 710 includes a correlation unit 712 and a combiner 714. Correlation unit 712 correlates the composite signal with a spreading code using the correlation delays selected from the candidate delays by a correlation delay selector 720 in response to weights determined by a weighting determiner 730. The weighting determiner 730 determines the weights in response to the channel and correlation characteristics, for example, a combination of a channel estimate and a quantity correlation estimate, such as a noise covariance estimate, determined by a determinator channel and correlation.
FIGURE 8 illustrates a signal processing apparatus 800 with an alternative segment equalizer structure in accordance with additional embodiments of the present invention. Apparatus 800 includes a symbol estimator 810 that processes a composite signal to generate a symbol estimate. Symbol estimator 810 includes a filter 812 that filters the composite signal and a correlator 814 that correlates the output of filter 812 with a spreading code. The derivatives of filter 812 are selected from a plurality of candidate derivatives by a filter derivative selector 820 in response to combining weights generated by a weighting determiner 830. The coefficients of filter 812 correspond to the coefficients (that is, weights ) for the selected shunts. The coefficient determiner 830 determines the coefficients in response to the channel and correlation characteristics of the composite signal determined by a channel and correlation determiner 840.
Candidate delays, eg, correlator and / or filter derivative delays, provided to signal processing apparatus such as those illustrated in FIGURE 5-8 can be generated in any of a number of different ways. For example, a "probing branch" approach can be used to generate candidate lags along the lines described in US Patent Application Serial No. Serial No. 09 / 845,950, filed April 30, 2001 (published as US Patent Application Publication No. US 2001/0028677) mentioned above.
ES 2 425 225 T3
Such an implementation is illustrated in FIGURE 9. As shown in FIGURE 9, a signal processing apparatus 900 according to some embodiments of the present invention includes a symbol estimator 910 that includes a correlation unit 912 that correlates a composite signal with a traffic channel spreading code, and a combiner 914 that weightedly combines the correlations produced by the correlator 912. The correlator 912 uses delays selected from a plurality of candidate delays by a correlation delay selector 920 in response to weights generated by a weighting determiner 930. The weights are generated based on the channel and correlation characteristics generated by a determinator. Channel and correlation 940. The candidate delays provided to the correlation delay selector 920 are generated by a polling unit 950. Polling unit 950 can identify candidate delays, for example, by correlating the composite signal with a pilot channel code, as described in the aforementioned US Patent Application Serial No. 09 / 845,950. It will be understood that other forms of identifying filter derivative or candidate lags may be used with the present invention.
FIGURE 10 is a flow chart illustrating exemplary signal processing operations in accordance with some embodiments of the present invention. Channel and correlation characteristics are determined for a composite signal that includes a desired signal along with the interference signals from one or more transmission sources (block 1010). The respective weights are determined for the respective of the candidate delays based on the channel and correlation characteristics for the composite signal (block 1020). A group of candidate delays is selected based on the weights, for example, by selecting those delays that have the highest associated weights or a desirable signal-to-noise estimate derived from the weights (block 1030). Here, "the highest associated weight" can be interpreted as the largest magnitude, the largest square magnitude, and so on. The composite signal information from the selected delays is processed in accordance with a spreading code to generate a symbol estimate for a desired signal in the composite signal (block 1040).
As an example, a maximum weighting criterion can be used to select delays, for example RAKE correlator delays or segment equalizer filter derivatives. Speaking in terms of a GRAKE structure, assuming a set of N candidate correlator delays has been identified, and given a correlation characteristic in the form of a noise covariance matrix Rn and a channel characteristic in the form of a vector of coefficients of channel cn for the N candidate delays, the combination weights wn for the candidate delays can be given by:
(2)
The combination weights wn can be determined using, for example, direct matrix inversion or another method for solving a linear system of equations (for example, the Gauss-Seidel method). A subset of the N candidate delays can be selected, according to some embodiments of the invention, by selecting those delays that have the largest associated weights.
FIGURE 11 shows exemplary signal processing operations according to such an approach. Channel coefficients and a covariance matrix are determined for a composite signal and a set of candidate delays (block 1110). The weights for candidate lags are generated from the channel coefficients and the covariance matrix (block 1120). The candidate lags having the highest weights are selected (block 1130). The composite signal is correlated to a spreading code at the selected delays (block 1140). The correlations produced are combined according to the recalculated weights to generate a symbol estimate (block 1150). A recalculation can be performed using (2) where N is replaced by the number of delays selected.
FIGURE 12 shows exemplary operations in an alternative segment equalizer implementation. Channel coefficients and a covariance matrix are determined for a composite signal and a set of candidate filter derivatives (block 1210). Weights for candidate filter derivatives are generated from the channel coefficients and the covariance matrix (block 1220). The candidate filter derivatives having the highest weights are selected (block 1230). The composite signal is filtered using a finite impulse response (FIR) filter with non-zero coefficients only for the selected shunts (block 1240). This can be implemented, for example, using a filter with programmable delays. The filter coefficients are obtained by recalculating the weights. The output of the FIR filter is correlated with a spreading sequence to generate a symbol estimate (block 1250).
It will be understood that the delay selection can be done in a number of different ways. For example, the weights can be ordered in ascending or descending order of magnitude and the first (or last) M lags selected. Alternatively, an iterative search technique can be used. For example, one could find the largest magnitude weight, select the associated delay, and remove that delay (and weight) from consideration. It will further be understood that "quantity correlations" other than the
ES 2 425 225 T3 noise covariance. For example, for least root mean square error (MMSE) combination, a generated data correlation matrix corresponding to pilot de-spread values could be used.
In accordance with aspects of the present invention, RAKE correlator delays, segment equalizer filter derivatives, or other delays can be selected in an incremental manner by determining a change in signal and noise content associated with adding particular delays or sets of delays. For the purposes of the following discussion, a G-RAKE structure is assumed, and a group of M candidate branches have already been selected. For such a set of M branches, a vector Mx1 c contains the corresponding channel derivatives and a matrix MxM R contains the corresponding correlation coefficients. The matrix R is Hermitian, and it is invertible, except in degenerate cases. A vector Mx1 w contains the combination weights for the respective M branches. The output of the combiner z is a weighted sum of the de-spread values, represented by a vector Mx1 r:
<img file="ES2425225T3_D0002.tif" />
For a combination weighted vector w, the signal-to-noise ratio (SNR) can be expressed as:
<img file="ES2425225T3_D0003.tif" />
For a G-RAKE implementation, the combination weights that theoretically maximize SNR can be given by:
<img file="ES2425225T3_D0004.tif" />
Therefore, the SNR can be given by:
<img file="ES2425225T3_D0005.tif" />
If you want to add a new branch to the selected group, the effect of adding the new branch in the SNR can be determined from the weights and noise covariance for the previously selected branches. The new branch placement persists in an updated channel wrapper vector c ':
<img file="ES2425225T3_D0006.tif" />
where χ represents a new channel wrapper corresponding to the new branch. The new correlation matrix R 'can be written as:
<img file="ES2425225T3_D0007.tif" />
where the vector Mx1 p contains the correlation coefficients between the old branches and the new branch and σ <sup>2</sup> is the noise variance of the new branch. The inverse R '<sup>-1</sup> of the new correlation matrix R 'can be written as:
<img file="ES2425225T3_D0008.tif" />
4-aR '<sup>1</sup>pp "R<sup>1</sup>
-ap<sup>H</sup>R- 'where a'<sup>1</sup> = σ<sup>2</sup> -p<sup>H</sup>R<sup>_1</sup>p (10).
Using equation (9), a new optimal weight vector can be given by:
<img file="ES2425225T3_D0009.tif" />
(9)
ES 2 425 225 T3
<img file="ES2425225T3_D0010.tif" />
where a weight increment vector Δ w is given by:
<img file="ES2425225T3_D0011.tif" />
due to the insertion of the new branch. The y represents a change to the old optimal weights w weighting of the new branch can be given by:
<img file="ES2425225T3_D0012.tif" />
Assuming that a "noise" branch, that is, a branch that does not correspond to an echo of the desired signal, is being evaluated for insertion, the channel% shunt can be set to zero, such that:
<img file="ES2425225T3_D0013.tif" />
For such a case, equation (23) can be simplified to:
<img file="ES2425225T3_D0014.tif" />
and equation (13) can be simplified to:
w = -ap<sup>H</sup>w. (16)
A new SNR γ 'can be expressed in terms of the old SNR γ, using equations (9) and (10):
<sub>r</sub>'= c'<sup>H</sup> R '-' c '^ + A /, (17) where the increase in SNR Δγ can be given by:
<img file="ES2425225T3_D0015.tif" />
The increase in SNR Δγ represents the change in SNR attributable to the insertion of the new branch.
Analysis of equation (18) reveals that the numerator can be maximized by matching the new correlation vector p with the old weight vector w, and that the denominator can be minimized when the new correlation vector p is matched with the old inverse of correlation R<sup>-1</sup>. Thus, to maximize the increase in SNR Δγ, the new correlation vector p can lie along the eigenvector of the largest eigenvalue of the old inverse of the correlation R<sup>-1</sup>. Because the old correlation R is invertible, it does not have a null space, thus, for this optimal condition, the new correlation vector p proposes to be in the null space of the old correlation R. This can be interpreted to mean that the new branch should provide information about a dimension not well covered by existing branches.
According to some embodiments of the present invention, a simplified technique for determining an increase in SNR that does not involve matrix inversion can be provided. A first order approximation w 'for the new weights can be given by:
-[;]· <.·>
ES 2 425 225 T3
Instead of setting the weight w for the new branch using equation (13), a value for the weight w can be determined that maximizes the SNR γ 'for w'. Using equations (4), (8) and (14):
<img file="ES2425225T3_D0016.tif" />
The numerator of equation (20) does not depend on the weight w. The denominator can be minimized by:
<img file="ES2425225T3_D0017.tif" />
which causes a maximum value for an approximate SNR γ 'given by:
<img file="ES2425225T3_D0018.tif" />
An increase in the approximate SNR Δγ 'can be given by:
<img file="ES2425225T3_D0019.tif" />
This expression may be easier to calculate than equation (18), since it does not require inversion of the matrix. Theoretically, the approximate SNR γ 'should be less than the SNR γ' calculated according to equation (17). If the number of old branches is not too small, then the approximate SNR γ 'can closely approximate the SNR γ' calculated according to equation (17). Therefore, the approximate SNR γ '(or the increment Δγ') can be used to evaluate the new branch.
FIGURE 13 illustrates exemplary operations for incrementally selecting G-RAKE branches in accordance with some embodiments of the present invention. It is assumed that one or more members of a set of lags have been selected, and that the associated weights and covariance matrix have been determined (block 1310). SNR estimates are generated for one or more candidate lags from the predetermined weights and the covariance matrix for the previously selected lags (block 1320). One or more new delays are selected based on the SNR estimates (block 1330), and the new delay (s) are used to process the composite signal (block 1340). The selection may be additive and / or it may involve substitution of a previously selected delay, for example, if the "old" delay was added by the incremental process, your estimate of the SNR can be retained in memory and compared to estimates of the Re-determined SNRs for new candidate branches to determine whether to replace the old delay with the new delay.
FIGURE 14 illustrates exemplary operations for incrementally selecting delays in accordance with additional embodiments of the present invention. Again, it is assumed that a set of M lags has already been selected from a plurality of L candidate lags, and that the associated weights and covariance matrix have been determined (block 1410). The SNR estimates for the remaining candidate LM lags are generated from the weights and the covariance matrix of the M lags (block 1420). These SNR estimates correspond to the set of M delays already selected plus an additional delay. The selected set of delays is updated by selecting the remaining candidate delays that have the highest SNR estimate (block 1430), and using the updated set of delays in processing the composite signal (block 1440).
An alternative incremental approach in accordance with further embodiments of the present invention is illustrated in FIGURE 15. A set of M lags is selected from a plurality of L candidate lags, and the associated weights and covariance matrix are determined (block 1510). The SNR estimates for the remaining candidate lags are generated from the weights and the covariance matrix for the previously selected lags (block 1520). A delay with the best estimate of the SNR is selected
ES 2 425 225 T3 (block 1530). If the desired number of new delays has been selected (block 1540), the updated set of selected delays is used to process the composite signal (block 1550). If not, however, new weights and a new covariance metric are calculated for the selected group of lags including the newly selected lag (blocks 1560, 1510), new estimates of the SNR are generated for the remaining candidate lags (block 1520) , and another new delay is selected (block 1530). The approach illustrated in FIGURE 15 may be more computer intensive than the operations of FIGURE 14, but it can take advantage of more information and in this way can provide more accurate results, for example, it can do a better job of avoiding redundant choices.
According to further embodiments of the present invention, an incremental approach may be implemented to select delays or shunts by treating groups of delays in aggregate form, ie, as "super branches". Due to complexity considerations, a receiver may not be able to evaluate each branch individually. To reduce complexity, the receiver could identify groups of branches to be evaluated as a group. If the group as a whole indicates a desirable level of SNR improvement, the group as a whole can be added to the selected set of branches without individually evaluating each branch of the group.
Exemplary operations for each approach are illustrated in FIGURE 16. A set of M lags is selected from a plurality of L candidate lags, and the associated weights and covariance matrix are determined (block 1610). An estimate of the aggregated SNR for a group (or groups) of the remaining candidate lags is generated from the weights and the covariance matrix for the previously selected lags (block 1620). The group of R delays with the best estimate of the SNR is selected (block 1630). If the update of the selected delays is complete (block 1640), the updated set, including the selected group of R delays, is used to process the composite signal (block 1650). If not, the updated weights and a new covariance matrix are determined (blocks 1660, 1610), the new SNR estimates are generated (block 1620), and a new set of lags is selected (block 1630). One integrity criterion is that the total number of available branches has been used. It will be appreciated that the group-based approach illustrated in FIGURE 16 can be combined with the individual evaluation approach of FIGURE 15, eg, super branches can be evaluated in conjunction with individual branches.
It can be pointed out that in determining the channel wrapper and correlation parameters for a super branch, the aggregation process can destroy useful information associated with the individual branches in the super branch. In other words, it is possible for the component branches to present a useful correlation with the already selected branches, but the correlation can cancel in the aggregation of the super branch. For the super branch, exact (eg equation (18)) or approximate (eg equation (23)) estimates of the SNR can be used. If the SNR estimate is large, it indicates that the group or subgroups are of interest. If the receiver has spare calculations, he may decide to investigate the individual branches in the group in detail. Alternatively, you can identify the group for further scrutiny in a future evaluation. If the SNR improvement is small, the recipient can discard the cluster. If a super branch provides significant SNR enhancement, it can be used directly in the G-RAKE combiner, that is, it is not necessary to treat the component branches individually in the combiner, as the same weighting can be applied to each.
A super branch can be viewed as an average of a number of branches. It can also be seen as a low pass combination, which can cause information loss that increases as the number of branches increases. This look can be extended using a Hadamard-like structure. For example, assuming a group includes 2<sup>j</sup> branches, you can apply a weighting vector + 1 / -1 to the branches and add the result. Hadamard sequences provide all (2<sup>J-1</sup>) the balanced sequences (same number of +1 and -1). These can be used to try and get a super branch with significant SNR enhancement. This can be seen as a simplified form of pre-join that uses only the +1 and -1.
Still other aspects of the present invention can be described in terms of a segment equalizer structure, although these approaches are also applicable to the selection of GRAKE correlator delays. Selecting combining branches on a G-RAKE receiver can be viewed as analogous to setting all coefficients of a segment equalizer FIR filter to 0 except for a small subset. The formulation of the segment equalizer can be done in the frequency domain.
FIGURE 17 illustrates a representative downlink structure for a spread spectrum signal (eg, IS-2000 and CDMA) for a terminal connected to a single base station. The nomenclature used in FIGURE 17 is as follows: x (t) represents the user spread / scrambled signal of order i; Ei represents the energy per symbol of the user signal of order i; hjx is the impulse response of the transmission filter; c (t) is the channel response that varies with time; hRx is the impulse response of the receive filter; yn (t) is the complex additive Gaussian white noise with variance No.
A colored noise matched filter for the system in FIGURE 17 is given by:
ES 2 425 225 T3 <sub>(24</sub>)
The + ΛΓ.
where Htx (C) is the Fourier transform of hrx, Hc (C)) is the Fourier transform of c (t), Xo (CC) is the Fourier transform of xo (t), and κ E, = XE ,. (25) * - /
In the context of the assumed system model and the assumed structure of the segment equalizer, the terms of equation (24) can be associated with the receive filter, the FIR filter or the weighting filter, and the correlator. These terms can be combined by inspection:
<img file="ES2425225T3_D0020.tif" />
<sup>Y</sup> correlator - Xq '(C)).
One problem is how to calculate a weighted frequency response in the weighting filter. This weighting filter can be given by (26).
For a given system, the product of Htx (C)) Hc (C)) Hr, and (C) is the Fourier transform HnetC) of the net channel coefficients. Hr v (C)) is typically exactly or roughly known at the receiver. Therefore, H tx (C)) H c (C)) can be calculated as follows:
<img file="ES2425225T3_D0021.tif" />
and only the signal energy Ei and the noise variance They are not necessary to calculate the frequency response ^ -Λ To obtain estimates of the signal energy Ei and the noise variance No, a procedure is used as described, for example , in US Application Serial Number 10/943274, filed September 17, 2005 and entitled "Method and Apparatus for CDMA Receivers" by Douglas A. Cairns and Leonid Krasny.
FIGURE 18 illustrates an exemplary method for selecting correlator delays or FIGURE 18 illustrates an exemplary method for selecting correlator delays or filter shunts using a weighted frequency response in accordance with some embodiments of the present invention. Channel coefficients, a receive filter response, signal energies, and a noise variance are determined (block 1810). A weighted frequency response (eg, equation (26)) is determined from these factors (block 1820). This weighted frequency response is converted to the time domain to produce a time domain weighted frequency response (block 1830). The delays of the FIR filter correlator (s) are selected based on the weights (block 1840). A composite signal is processed using the selected delays or shunts (block 1850).
The block and flow diagrams of FIGURES 5-16 and 18 illustrate the architecture, functionality, and operations of possible implementations of the computer program apparatus, methods, and products according to various embodiments of the present invention. It should also be noted that, in some alternative implementations, the actions outlined in the diagrams may occur outside of the order outlined in the figures. For example, two operations shown in succession may, in fact, be executed considerably concurrently, or the operations may sometimes be executed in the reverse order, depending on the functionality involved.
Additional variations of the above-described computer program apparatus, methods, and products are also within the scope of the present invention. For example, techniques that use “correlations of
ES 2 425 225 T3 quantity ”, for example noise covariance or data correlations, can obtain such correlations using parametric or non-parametric approaches. A nonparametric approach may involve, for example, using a set of probing branches or existing branches to measure quantity correlations. A parametric approach may involve, for example, the calculation of a noise correlation using channel estimates and / or other quantities.
A conventional nonparametric noise covariance estimator that can be used with the present invention is described in US Patent No. 6,363,104 to Bottomley et al shown in FIGURE 19. Channel estimates are provided as an elimination signal unit 1910, which subtracts channel estimates from de-spread values (eliminated modulation) to form error values. An error processor 1920 receives the error values and includes a noise correlation computer 1922 in which the errors are multiplied by the conjugates of the other errors to produce noise correlation values. These noise correlation values are then provided to a smoother 1924 that averages the values over time, eg, multiple bins.
A parametric noise covariance estimator that can be used with the present invention is described in US Application Serial No. 10 / 800,167, filed March 12, 2004, entitled "Method and Apparatus for Parameter Estimation in a Generalized Rake Receiver ”, shown in FIGURE 20. An elimination signal unit 2010 produces an error signal that is used to perform a noise correlation measurement on a 2022 noise correlation computer on a 2020 subprocessor. The measurements are fixed to a noise covariance model that includes elements structure provided by a structure element computer 2024 and adjustment parameters determined by a G-RAKE parameter estimator 2026. The fit parameters and structure elements are combined by a noise covariance computer 2028 to produce a noise covariance estimate.
For nonparametric approaches, branches can be placed on candidate lags to measure data or noise correlations. For a segment EQ, samples can be correlated to other samples based on candidate delays. For parametric approaches, a concept of "virtual" probing branches can be introduced, that is, a parametric approach may allow evaluation of candidate delays or shunts even if the information of the actual corresponding physical delays or shunts is not available.
It will further be appreciated that the present invention also encompasses embodiments in which multiple receiving antennas are used. For example, branch or shunt selection could be done on an antenna-by-antenna basis, or combined quantity correlations could be used to select delays from multiple antennas. The present invention also covers embodiments in which transmission diversity is provided. For example, for transmit diversity with feedback, pilots from multiple transmit antennas could be used to calculate composite channel estimates. For smooth handover, weighted solutions could be calculated separately, and used to select from a fused set of candidate lags. Alternatively, a joint SNR metric could be used. For transmit diversity using an Alamouti code, the same branch selection could be used for both transmitted signals. For multiple input, multiple output (MIMO) applications, the delay selection can be done separately for each signal, or an approach that maximizes the minimum SNR could be used.
In the drawings and specification, typical illustrative embodiments of the invention have been described and, although specific terms are employed, they are used in a generic and descriptive sense only and not for purposes of limitation, the scope of the invention set forth in the following claims.
Contents10
36 sheets
Sheet 1 Sheet 2 Sheet 3 Sheet 4 Sheet 5 Sheet 6 Sheet 7 Sheet 8 Sheet 9 Sheet 10 Sheet 11 Sheet 12 Sheet 13 Sheet 14 Sheet 15 Sheet 16 Sheet 17 Sheet 18 Sheet 19 Sheet 20 Sheet 21 Sheet 22 Sheet 23 Sheet 24 Sheet 25 Sheet 26 Sheet 27 Sheet 28 Sheet 29 Sheet 30 Sheet 31 Sheet 32 Sheet 33 Sheet 34 Sheet 35 Sheet 36
38 members in 12 offices
Priority claims9
| Document | Office | Kind | Date |
|---|---|---|---|
| 959923 | United States of America | – | |
| 95992304 | United States of America | A | |
| 95992304 | United States of America | A | |
| 2005010646 | European Patent Office (EPO) | W | |
| 2005010646 | European Patent Office (EPO) | W | |
| 959923 | – | – | – |
| PCTEP2005010646 | – | – | – |
| US20040959923 | – | – | – |
| WO2005EP10646 | – | – | – |
Members38
| Document | Office | Kind | |
|---|---|---|---|
| WO0129982A1 | World Intellectual Property Organization (WIPO) | A1 | |
| AU7071300A | Australia | A | |
| US2001028677A1 | United States of America | A1 | |
| WO02052743A2 | World Intellectual Property Organization (WIPO) | A2 | |
| EP1222747A1 | European Patent Office (EPO) | A1 | |
| WO02052743A3 | World Intellectual Property Organization (WIPO) | A3 | |
| JP2003512758A | Japan | A | |
| CN1411635A | China | A | |
| EP1344327A2 | European Patent Office (EPO) | A2 | |
| US6683924B1 | United States of America | B1 | |
| WO02052743A9 | World Intellectual Property Organization (WIPO) | A9 | |
| US2005078742A1 | United States of America | A1 | |
| EP1222747B1 | European Patent Office (EPO) | B1 | |
| AT295999T | Austria | T | |
| ATE295999T1 | Austria | T1 | |
| DE60020256D1 | Germany | D1 | |
| US6922434B2 | United States of America | B2 | |
| WO2006037593A1 | World Intellectual Property Organization (WIPO) | A1 | |
| US2006182204A1 | United States of America | A1 | |
| KR20070060116A | Republic of Korea | A | |
| EP1800417A1 | European Patent Office (EPO) | A1 | |
| WO2007115581A1 | World Intellectual Property Organization (WIPO) | A1 | |
| CN101069362A | China | A | |
| TW200746737A | Taiwan Province of China | A | |
| JP2008516491A | Japan | A | |
| EP2005610A1 | European Patent Office (EPO) | A1 | |
| CN100449956C | China | C | |
| US7769078B2 | United States of America | B2 | |
| US7778312B2 | United States of America | B2 | |
| JP4559002B2 | Japan | B2 | |
| CN101069362B | China | B | |
| JP4829239B2 | Japan | B2 | |
| KR101156876B1 | Republic of Korea | B1 | |
| EP1344327B1 | European Patent Office (EPO) | B1 | |
| EP1800417B1 | European Patent Office (EPO) | B1 | |
| EP2605415A1 | European Patent Office (EPO) | A1 | |
| DK1800417T3 | Denmark | T3 | |
| ES2425225T3This record | Spain | T3 |
Numbers
- Publication
- 2425225
- Publication, DOCDB
- 2425225
- Publication, EPODOC
- ES2425225T
- Application
- 5795998
- Application, DOCDB
- 05795998
- Application, EPODOC
- ES20050795998T
Titles2
- Spanish
- Aparato, métodos y productos de programas informáticos para selección de retardo en un receptor de espectro ensanchado
- English
- Device, methods and software products for delay selection in a spread spectrum receiver
Classification
- CPC, 4
- H04B1/712
- H04B1/709
- H04B1/7117
- H04B2201/709727
- IPC, 3
- H04B1 7117
- H04B1 707
- H04B1 712