Multiuser detector for variable spreading factors

Variable expansion factor multi-user detector technology field

[0001] The present invention generally relates to a multiple access digital communication system. In particular, the present invention relates to a multi-user detector system and a method for simultaneously receiving data from multiple users with different spreading factors.

Background technique

[0002] A multiple access communication system allows multiple users to access the same communication medium to transmit or receive information. This medium may include, for example, a network cable in a local area network or LAN, a copper cable in a traditional telephone system, or an air interface used in a wireless communication system.

[0003] A conventional multiple access communication system is shown in FIG. 1. This communication medium is called a communication channel. Communication technologies, such as frequency division multiple access, or FDMA, time division multiple access, or TDMA, carrier sensing multiple access or CSMA, code division multiple access or CDMA, and other technologies, allow more than one user to share the same Communication medium for access. These technologies can be mixed and used to produce mixed changes in multiple access methods. For example, the time division duplex or TDD mode of the third-generation W-CDMA standard is a combination of TDMA and CDMA.

[0004] An example of a conventional CDMA communication system is shown in FIG. 2. CDMA is a communication technology that transmits the data in a spread spectrum (spread spectrum) by modulating the data to be transmitted with a pseudo-noise code. The data signal to be transmitted may only have a bandwidth of several kilohertz distributed in a frequency band of several million hertz. This communication channel is used by K independent sub-channels at the same time. For each sub-channel, all other sub-channels present interference.

[0005] As shown, a single sub-channel of a predetermined bandwidth is mixed with a unique spreading code, and the spreading code is repeatedly generated by a wide-band, pseudo-noise (PN) sequence generator Of a predetermined pattern. These unique user expansion codes are usually similar to each other perpendicular to each other, so the cross-correlation between the expansion codes is close to zero. A data signal is modulated with a PN sequence that generates a digital spread spectrum signal. A carrier signal is then modulated with the digital spread spectrum signal and transmitted according to the transmission medium. A receiver demodulates and extracts the transmission of the digital spread spectrum signal. The transmitted signal is regenerated after being correlated with the matched PN sequence. When the expansion codes are perpendicular to each other, the received signal can be related to a specific user signal related to the specific expansion code. Therefore, only the desired user signal related to the specific expansion code is enhanced, and the signals of all other users Other signals have not been strengthened.

[0006] Each value of the spread code is called a chip, and has a chip rate that is the same as or greater than the data rate. The ratio between the chip rate and the sub-channel data rate is the spreading factor_o[0007] In order to expand the possible range of data signal values, a symbol is used to represent digital values greater than binary. The three and four values use ternary and quaternary symbols respectively. The concept of symbols allows a greater degree of information, because the bit content of each symbol indicates a unique pulse shape. Depending on the symbol used, there are the same number of unique pulses or waveforms. The information at the source is converted into symbols, and the symbols are modulated and transmitted via sub-channels to be demodulated at the destination.

[0008] The spreading code in the CDMA system is selected to minimize the interference between a desired sub-channel and all other sub-channels. Therefore, the standard method of demodulating the desired sub-channels is to call all other sub-channels as interference, similar to showing its own interference in the communication medium. The receiver designed for this program is a single user, matched filter and RAKE connection

Receiver.

[0009] Because different sub-channels do interfere with other sub-channels somewhat, another method is to demodulate all sub-channels at the receiver. The receiver can listen to all users of one transmission by executing the decoding algorithm of each sub-channel in parallel. This concept is called multi-user detection. Multi-user detection can provide important performance improvements in single-user receivers.

[0010] Referring to FIG. 3, which shows a system block diagram of a conventional CDMA receiver using a multi-messenger detector. The receiver can include such functions, such as radio frequency or RF down conversion and related filtering of radio frequency channels, analog to digital conversion or optical signal demodulation of a specific communication medium. The output of the receiver is a processed signal, either analog or digital, and includes an expanded signal of all active sub-channels. The multi-user detector performs multi-user detection and outputs multiple signals corresponding to each active sub-channel. All or a number of sub-channels smaller than the total number can be processed.

[0011] The ideal multi-user detector is an enhanced computing device that executes several complex arithmetic operations, so it is difficult to implement economically. In order to minimize the cost, sub-ideal multi-user detectors, such as linear detectors, have been developed, requiring less computational complexity when the compromise is close to the ideal detector performance. Linear detectors include decorrelator, minimum mean square error or MMSE detector, and 0 forced block linear equalizer or ZF-BLEso

[0012] FIG. 4 shows a conventional linear multi-user detector for synchronous or asynchronous CDMA communication. The data output from the communication media specific receiver (shown in Figure 3) is coupled to a sub-channel evaluator used to evaluate the impulse response of each transmitted symbol in the individual sub-channel. The linear detector uses the impulse response and a sub-channel evaluation spread code to demodulate the data of each sub-channel, and this data is output to the sub-channel data processing block of the individual user.

[0013] In order to perform parallel detection of K sub-channel users in the physical system, a linear multi-user detector method is implemented, such as fixed gate arrays, microprocessors, digital signal processors or DSPs and the like. The fixed logic system allows greater system speed, while the microprocessor-oriented system provides programming flexibility. Responsible for the execution of a series of arithmetic operations for each implementation of the multi-user detector. To describe this function, the following variables usually define the structure and operation of a linear multi-user detector:

[0014] K=the total number of active users/transmitters in the system

[0015] Nc=-the number of chips in the data block. The number of chips is required because of the variable expansion factor, and this number is the common point of measurement for all users.

[0016] The impulse response length of the communication channel in the anal code chip. This is usually a predetermined parameter of the system.

[0017] Q^(k)= The expansion factor of user k. The expansion factor is equal to the number of chips used to expand a symbol of the user data. The system knows this unfolding factor in advance and does not need to evaluate them from the received data.

[0018] Ns is the number of symbols transmitted by user k. Ns is called Nc/Q®.

[0019]

Ns^T = ^Ns^fk>= The total number of symbols transmitted.

k=l

[0020] d^(k)= Data (information) transmitted by user k. The data is presented in the form of vectors, where a vector is a data matrix indicated by a single index variable. For the purpose of vector and matrix operations, all vectors are defined as column vectors. d^(k)The first element of Ι?¹¹The juice delivered by the user¹¹Symbol.

[0021] = The impulse response of the sub-channel experienced by the user expressed as a vector. This amount needs to be evaluated at the receiver. The receiver evaluation of the sub-channel impulse response is called h^(kThe element h® of the vector is generally multiple, which has the amplitude and phase variables imported by the sub-channel.

[0022] v^(k)= The expansion code of user k, expressed as a vector. For the purpose of linear multi-user detection, it is useful to consider a vector that includes a section of the unfolding code that unfolds a specific symbol. Therefore, the vector ν%® is defined as used to expand by I?¹¹Juice sent by the user¹¹The expansion code of the symbol. In terms of mathematics, it is defined as

[0023] v^ⁿ⁾=^^k), ΜAt(nl)Q^(k)+l#I#nQ^(k), And 0 for all other i, where i is the index of the vector element.

[0024] On behalf of the user k data, from the unfolding sequence v^(k)Expanded and transmitted via the messenger sub-channel h®.

The vector r® represents the channel observation during the cycle time when a data block arrives.

[0025] vector r^(k)The i^thThe element can be defined as

[0026] Strict = £ Ye »He often · Procedure 1

[0027] The signal received at the receiver includes all user signals r® plus noise. Therefore, we can define the received data vector r as follows

K

[0028] rr^(k) + η program 2 k=l

[0029] The vector n of the program 2 represents the noise introduced by the communication channel.

[0030] FIG. 5 shows a system and method of a conventional linear multi-user detector. Sub-channel impulse response vector h to be evaluated^(k)And expansion code v^(k)It is used to generate the system response matrix for each user k. A matrix is a digital block indicated by two index variables and is arranged in a rectangular grid. The first index variable is a row index, and the second index variable is a column index.

[0031] The system response matrix of user k is usually indicated as A^(k\ In the strict line, the mang column element is indicated as a "3 and is defined as

W

[0032] 4/ = Σ Ding Eating: Program 3

JS: l.

[0033] Each column of the matrix A® corresponds to a matched filter response for a specific symbol transmitted by user k during the desired period. Referring to Figure 5, the received data r matches the combination of all user expansion codes and sub-impulse responses. Therefore, Α® contains the Ns® matched filter response. A^(k)The columns are the following

Ό 0

[0034] <'=attached

[0035] Procedure 4

[0036] where each vector has dimensions

[0037] Q^(h)+W-1 Program 5

And offset from the top of matrix A®

[0039] (nT) · Q^(k)

[0040] Because the expansion code is not periodic in symbol time; for i, j, and b⁽j^k). Vector elements that may have non-zero values are called vector supports. Therefore, the watt Q is the support of 47'.

[0041] Once the system response matrix of each user is generated, a full system response matrix, called A, is connected by

The system response matrix for all users is generated as shown below:

[0042] A = [A,...,A^(k),..., A®] program 7

[0043] According to the conventional modulation technology, there may be multiple elements of h®. There can be multiple non-zero elements following A. An example of all system response matrices for conventional detectors based on the assumptions of procedures 4, 5, 6, 7 is

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[0045] For 2 users (k=2), A and A have 16 chips in a data block (Nc=16), and the length is

The channel impulse response of 4 (W=4) and an expansion factor of the two first users (Q=2) and an expansion factor of the four second users (Q=4). Indicate the i-th of the combined system in the generated total system response matrix A^thElement and kth^thUser's n^thSymbol's channel response.

[0046] The received data r is processed using a bank of all system response matrices A representing the matched filter response to generate a vector of the matched filter output, which is represented by y. The matched filtering operation is defined as

[0047] y = A^Hr program 9

[0048] Matrix A¹¹Represents the Hermitian (or multiple) transformations in matrix A. The conversion is defined as 4, =^Αβ where the upper horizontal line represents the operation of taking one or more conjugates. The matched filter output is then multiplied by the inverse of a destination matrix 0. The target matrix ο represents an operation to distinguish the type of each linear receiver mode. It is derived from matrix A. [0049] The zero-forced block linear equalizer (ZF-BLE) receiver has a designation of 0=A^HA linear receiver for a target matrix of A. The minimum mean square error block linear equalizer (MMSE-BLE) receiver is a linear receiver with a designation of ο = Α^ηΑ+ σ ²The target matrix of 1, where σ ²For the noise change that appears on each symbol of the received data vector r, the matrix I is the identity matrix _o An identity matrix is a square and symmetric matrix, with 1 on its main diagonal and 0 elsewhere. The size of the identity matrix is chosen so that additional calculations are valid according to linear algebra.

[0050] For a decorrelator (decorrelation receiver), the matrix A is simplified by ignoring the channel response h® and only considering the spreading codes and their cross-correlation (interference) characteristics. A cross-correlation matrix is usually called R, usually to connect the phase

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The switch type receiver is constructed. This matrix can be constructed by assuming that in the definition of A above and Ming=1 (that is, the channel response of each sub-channel is a pulse). Subsequently, the cross-correlation matrix R is the target matrix 0, as defined for the ZF-BLE receiver. A decorrelator is usually used as a one-time process of a more complex multi-user detection receiver. Once the target matrix is generated, the multi-user detector will invert this matrix and mark it as 0

[0051] The inversion of the target matrix is then multiplied by the matched filtered output vector y to generate an evaluation of the data vector d, where d (evaluation)=0^0. The inversion of the target matrix is a complex and computationally inverse process. The number of operations required to perform this processing increases with the cube of the size of matrix 0. For most asynchronous CDMA receivers, the size of 0 is very large, which makes the reversal processing difficult to achieve.

[0052] To overcome this limitation and make the system practically reliable, Cholesky's digital method is used. Cholesky decomposition can effectively reduce the computational complexity of matrix 0 if the matrix is banded.

[0053] A banded matrix is a square matrix that only includes non-zero values at a few diagonal corners away from the main diagonal. The number of non-zero diagonals with at least one non-zero element close to the main diagonal is called bandwidth. Therefore, a symmetric matrix M is called a band with a bandwidth ρ, if

[0054] πι_υ· = 0, for all j&gt; i+p program 10

[0055] where m" is an element of M, i is a row index and j is a column index. For a band matrix with size η and bandwidth ρ, Cholesky decomposition can reduce the required inverse digital operation of the target matrix 0 From the cube η with the size of the matrix³Changes to npS changes as the size of the matrix is multiplied by the square of the bandwidth.

[0056] As discussed above, the target matrix of the ZF-BLE receiver is 0=A%. To illustrate the complexity of the numbers, the overall system response shown in program 6 in the target matrix of matrix A is

X.

[0057] ο

Q ¥

Λ[0058] where 0 means that all arithmetic operations produce 0 and X represents a non-zero value. If the non-zero elements of the strict row and the strict column of the overall system response matrix A do not have the same vector index, the corresponding element of the target matrix 0 with row index i and column index j will have a bandwidth of 0. 0 ( Program 11) is equal to 9, because there are no non-zero elements outside the 9 columns away from the main diagonal.

[0059] The target matrix 0, as it is in the conventional receiver shown in FIG. 5, is not properly banded. Therefore, Cholesky decomposition cannot be effectively used to reduce the complexity of calculations when inverting matrix 0. However, the prior art discloses that when all users transmit with equal expansion factors, the rearrangement of the overall system response matrix A can be performed before calculating a target matrix 0 and adjusting the matrix 0 to a band matrix. The system block diagram of this process is shown in Figure 6o

[0060] The process of calculating the rearrangement of the columns of the matrix A performs the rearrangement without requiring any additional information. This rearrangement reduces the computational complexity when arranging the inversion matrix. Once the detection process is completed, a user data vector d is calculated, a reverse rearrangement process is performed, and the descrambling vector d is returned to its original form for further processing.

[0061] In a typical asynchronous CDMA system, a rearrangement target matrix is at least 10 times smaller than its original size. Therefore, a saving of at least a factor of 100 in the processing time can be achieved when the Cholesky decomposition is performed on a target matrix based on a rearranged overall system response matrix. However, the prior art does not disclose the rearrangement method used when using different expansion codes among multiple active users.

[0062] Therefore, it is desirable to reduce the complexity of multi-user detection.

Summary of the invention

[0063] Multiple communication signals have different spreading codes. Each communication has an associated code including chips. For each chip of each communication, a vector of chips convolved with an impulse response is generated. For each communication, a support block including a chip vector is generated. The number of chip vectors in a support block is based on the expansion factor of the communication. A system response matrix is combined. The system response matrix has a sub-matrix of symbols. Each symbol sub-matrix includes a supporting block from each communication. The communication data is detected using the symbol matrix.

Description of the drawings

[0064] FIG. 1 is a schematic block diagram of a conventional multiple access communication system.

[0065] FIG. 2 is a schematic block diagram of a conventional CDMA communication system.

[0066] FIG. 3 is a schematic block diagram of a conventional CDMA receiver with multi-user detection.

[0067] FIG. 4 is a schematic block diagram of a conventional multi-user detector.

[0068] FIG. 5 is a block diagram of a conventional linear multi-user detector.

[0069] FIG. 6 is a block diagram of a conventional linear multi-user detector using Cholesky decomposition.

[0070] FIG. 7 is a block diagram of the linear multi-user detector of the present invention.

[0071] FIG. 8 illustrates the system response matrix A^(k)Up to the following offset.

[0072] FIG. 9 illustrates the assignment of matrix column index values.

[0073] FIGS. 10A and 10B are flowcharts of another method for implementing the present invention.

[0074] FIG. 11 illustrates the steps of assembling an expansion factor group matrix.

[0075] FIG. 12 illustrates the steps of combining an AN matrix according to the present invention.

[0076] FIG. 13 illustrates another combination of a system response matrix.

[0077] FIG. 14 illustrates a k^thSystem response matrix of resource units, A_ko

[0078] FIG. 15 illustrates the first supporting block of a resource unit, B(Z.

[0079] FIG. 16 illustrates the steps of combining another system response matrix A.

Detailed ways

[0080] The embodiments will be described with reference to the accompanying drawings, in which the same numbers represent the same components.

[0081] Shown in FIG. 7 is a multi-user detector 17 that detects multiple users transmitting in a common CDMA channel after reception. The multi-user detector 17 includes a plurality of processors with auxiliary memory for performing various vector and matrix operations. Another embodiment includes fixed gate arrays and DSPs that perform the different processor functions. Detector 17

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It also includes a first input 19 for inputting the impulse response of individual k sub-channels called the vector h® to evaluate to the correct intermediate symbol interference or ISI caused by the symbol of a sub-channel itself and multiple access interference or caused by The MAI of all received data signals caused by symbols from other users' sub-channels,-the second input 21 is used to input all users from all transmissions within a discontinuous block time, including those from each user Data in the form of an input vector r of the combined data of the resource channel, and an output 23 for outputting user data d® in the form of an output vector from the received channel data r for each user k. User K and the expansion factor Q for each user (k = 1, 2, 3, -K)^(k)41 is one's own knowledge.

[0082] In order to obtain user data d® of a specific user from the combined user data r, the user data must be filtered using a matched filter 25 or the like. Those skilled in the art recognize that a matched filter 25 requires a response characteristic, which is a combination of unfolding pulse shape and user sub-channel impulse response in multiple conjugates in order to generate an output that represents the signal level before transmission. A signal input to the filter 25 that does not match a predetermined response characteristic produces a lower output.

[0083] Each independent k sub-channel impulse response evaluation h^(k)It is input into a first memory 27, where it is combined with the same user expansion code 29 (procedure 3) that generated the user's system transmission response evaluation matrix A®. An arrangement processor 33 of the multi-user detector 17 performs all matrix 4/row reordering. This arrangement method requires that each sub-channel system response matrix A® has a column structure defined by program 4, which is a typical linear receiver. If the system response matrix A^(k)Instead of the format defined by the program 4, the arrangement processor 33 first rearranges the structure defined by the program 4 in some columns. Multi-user detector 17 does not require all system responses in matrix A^(k)It is concatenated as an overall system response matrix A as defined in Procedure 7.

[0084] The arranger 33 checks each system response matrix Α, Α, Α. . As mentioned earlier, each system response matrix A® has the same number of rows; only the number of columns changes. As shown in FIG. 9, the arrangement processor 33 assigns an index value ni to each column of each system response matrix A® based on its respective upper 0®Tn and lower 0®Bn effects. This column value is assigned in order of increasing size from the column with the smallest upper offset with the largest lower offset to the column with the largest upper offset with the smallest lower offset.

[0085] If one of the two rows encounters a larger upper shift and a larger lower shift than the other, if the difference between the upper shifts is greater than the difference between the lower shifts, it has a lower upper shift The shifted column is assigned a lower index ni. If the difference between the lower offsets is greater than the difference between the upper offsets, the column with the larger lower offset is assigned a lower index ni. If the difference between the upper and lower offsets is the same, one of the two columns can be assigned a lower index nio

[0086] The arrangement processor 33 combines an overall system response matrix AN into the order of the assigned column index ni. This column index ni is maintained in the memory 33 for use during the descrambling process 45. For example, using the overall system response matrices A and A shown in program 8, the arrangement method 17 of the present invention generates the overall system response matrix A as follows:

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[0088] This arrangement method instructs the 8 columns (1-8) of the system response matrix A and the four columns (9-12) of the system response matrix A to generate a well-banded overall system response matrix A (procedure (2).

[0089] The above-mentioned arrangement method embodiment includes each system response matrix A, A, A...A^(K)Check the upper 0®Tn and lower 0®Bn offsets of each column and every other column. Assuming that each system responds to the specific structure of the matrix Α®, that is, the columns of each matrix are arranged in the order of increasing upper offset and decreasing lower offset, when advancing from left to right (refer to program 8, matrix Α,Α), another method 199 can be executed without directly checking the response matrix A of each system^(K) ο

[0090] Another method 199 is shown in FIGS. 10A and 10B. All system response matrices A® corresponding to users with equal expansion factors (step 201) are clustered together (step 203). For each expansion factor group g, the memory is configured in the processor and can store all the columns from all system response matrices A, A, A...Α®. The expansion factor group g is arranged in the order of increasing expansion factors.

[0091] The exemplary system illustrating the performance of this other method 199 includes 7 with 4 different expansion factors Q assigned as follows^(K):

[0092] User 1 (Q)=8 User 2 (Q)=8 User 3 (Q)=8 User 4 (Q)=32

[0093] User 5 (Q)=16 User 6 (Q)=16 User 7 (Q)=4

[0094] Using another method of system and method 199, the system response matrix A® is separated into expansion factor groups:

[0095] Group 1 (Expansion Factor 4)

[0096] Group 2 (Expansion Factor 8)

[0097] Group 3 (Expansion Factor 16)

[0098] Group 4 (Expansion Factor 32)

A

A, A, A

AA

A'

[0099] A further expansion factor group g includes at least one system response matrix A^(K), Where each matrix A^(K)Is from 1 to

L^(G)Arbitrary index. Each expansion factor group g is indexed according to the increased expansion factor size.

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[0100] In each expansion factor group, the related system response matrix A® is combined into a common expansion factor group transmission response matrix bin', where g=1, 2, 3, -0 (step 205). As shown in Fig. 11, method 199 copies the first column of the system response matrix with index 1 to the first blank column of Zhe, and the first column of the system response matrix with index 2 to almost the second blank column; The expansion factor group g continues to follow the rest of the system response matrix until all the first columns are copied. Method 199 is performed by copying the second column, third column, etc. of each matrix A® in the individual expansion factor group box.

<td>[0101]</td><td>All matrices in the expansion factor group g have the same number of columns due to the same expansion factor. Therefore, the combination</td>

The expanded group factor group transmission response matrix C will have L times the number of columns in the relevant system response matrix A®.

<td>[0102]</td><td>An overall system response matrix AN that combines the expansion factors of the combination and interaction, and the expansion with the lowest expansion factor</td>

The group factor group transmission response matrix is continuously copied into the memory (step 207), starting with the first column, that is, the first column of 4/, to the column of the first configuration of AN. The expansion group factor group transmission response matrix with the lowest expansion factor £/P has the largest number of columns. All other expanded group factor group transmission response matrices will be inserted into this basic matrix AN.

<td>[0103]</td><td>If the system expansion factor is other even integer multiples (step 209), the processor 33 considers the remaining</td>

Expand the group factor group transmission response matrix core (step 209) to combine the overall system response matrix AN in any order (step 209)

211). For each expanded group factor group transmission response full matrix &amp; column, the processor 33 drives a column of displacement reference index m,

<td>[0104]</td><td></td>

<td>[0105]</td><td>Which represents the group transmission response matrix of the expansion group factor under consideration £The expansion factor related to Q table</td>

Shows the lowest expansion code among all groups, η is the column of the group transmission response matrix of the expansion group factor under consideration, where n=l,

2, 3,...N (Step 211) ο

<td>[0106]</td><td>In order to use the column displacement index m, use the establishment of the expansion group factor group transmission response matrix with the lowest expansion factor</td>

The total number of the system response matrix L is derived from a reference position in AN (step 215)

<td>[0107]</td><td>mHL Program 14</td>

[0108] Under consideration, the processor 33 uses the system response matrix belonging to the unfolding factor group currently under consideration to transmit the response matrix from the unfolding factor group.⁸Export a list of sets (step 217),

[0109] L^(G)H(nl)+l to L^(G)Hn program 15

[0110] The processor 33 copies the column set defined by the program 15 and inserts it into the basic matrix AN after the column of the ship with the reference position defined by the program 14, as shown in FIG. 12. The remaining columns of the expansion factor group matrix under consideration are likewise copied and inserted into the basic matrix AN (step 211). After all the columns from one expansion factor group matrix are replaced, the processor 33 selects the next expansion factor group matrix 4/F (step 223) and executes the above method. Programs 13, 14, 15 allow the group transmission response matrix from the remaining unfolded group factors &amp; Yin's i^thColumns are placed in AN with similarly supported juice¹¹After the column (step 225).

[0111] When the system expansion factor is not other even integer multiples, the right side of the program 13 indicates that an integer is not generated. In this case, the processor 33 will approximate the result of the program 13 to the nearest integer above or the nearest integer below this value (step 213). This approximation direction has a negligible effect on the overall system performance. The remaining group system response matrix &amp; the order of different considerations may have some impact on system performance. The knowledge of the conventional unfolding factors can be used to select the appropriate order in advance.

[0112] Using the permutation technique described above, and for the case when the expansion factors are even integer multiples of each other, a moment

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The array bandwidth B can be achieved, which can be expressed as:

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[0113]

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'Program 16

[0114] Program 16 predicts that the bandwidth of the overall system response matrix of program 11 will be 3 and 6. The inspection of program 12 reveals that the bandwidth after 199 for each arrangement method is 4o

[0115] This improvement becomes more obvious as the number of transmitted symbols increases. If the system transmits 16000 chips of the first user (800 symbols of the first user and 400 symbols of the second user), matrix A^hThe bandwidth of A will be approximately 800. Use this arrangement method to generate an overall system response matrix A, AN^hThe bandwidth of AN remains 4, because the bandwidth (program is independent of the number of transmitted symbols. After all the elements of the target matrix 0 have been derived, the inversion 41 is performed. Because of the complexity and bandwidth of inverting a matrix The square is proportional, the present invention 17 provides an approximation (800/4)² = 200² = The reduction of the computational complexity of the factor of 4 0 0 00.

[0116] The overall system response matrix AN provides response characteristics to the matched filter 25. Each column of the system response matrix AN is a vector representing the response characteristic of a specific symbol. The received data vector r is input to the matched filter 25, where it is matched with each response feature from the overall system response matrix AN to generate a matched filter output vector y. Each element of the output vector y corresponds to a preliminary evaluation of a specific symbol transmitted by a predetermined user. The output vector y from the matched filter 25 is loaded into a multiplier 43 with an inversion target matrix 0. The matched filter 25 output vector y and the inversion target matrix 0 are multiplied together to generate a user data vector d_oThe user data vector d contains all data transmitted from all users during the discontinuous time block. Because the output of the target matrix 0 and the matched filter 25 is based on the overall system response matrix AN, the user data vector d must be descrambled. This descrambling procedure is the reversal of permutation method 199.

[0117] A descrambler 45 rearranges each element of the user data vector d based on the row rearrangement performed, when undergoing the arrangement method 199. The elements of the data vector d are in the same order indicated by the overall transmission response in the matrix A, 1,9,2,3,10, 4,5,11,6,7,12,8, vertically shifted items (transposed vertically ) The descrambler 45 configures the memory space with the same size and places each vector element in a consecutive order of 1-12. After the user data vector d is descrambled, the user data is output 23 for further processing.

[0118] Another method of reducing the bandwidth of the system response matrix A is shown in FIG. 13, FIG. 14, and FIG. 15, and is explained compared to the flowchart in FIG. 6. Figure 13 illustrates the system response matrix A. The A matrix is set so that it has an S symbol sub-matrix. S is the minimum number of symbols, so a data area of a resource unit in the system may have S = N/Q. Nc is the number of chips in the data area. Qmax is the maximum expansion factor of the system, for example, an expansion factor of 16. To illustrate the time-sharing duplex burst pattern 2, Nc is 1104 and a maximum delay expansion Qmax is 16. Therefore, the A matrix contains the N/Q^th order matrix.

[0119] Each time the matrix has a supporting block B for each of K received resource units^(s'^k\ s represents the sub-matrix of symbols from 1 to S, and k represents the number of resource units from 1 to K.

[0120] For each resource unit, a system response matrix can be established. Each symbol of the resource unit of this matrix has a column, N/Qk column. Qk is the expansion factor of km-th resource unit. Each row has a strict row of blocks 8. Each block has a column with a length of the resource unit symbol impulse response length Lr plus 1, Lr+L· For the first block B (leftmost) of the matrix, the upper part of the block is the upper part of the matrix. Each block is a symbol, Qk, whichever is lower in the matrix. To illustrate, the column block in the second column 8 is a Qk chip lower than 8 in the matrix.

[0121] Each column of block eight (1) corresponds to the first?¹¹A strict symbol of the resource unit. It is derived by multiplying the scrambling code's strictest sector and the Phth resource unit chip-by-chip with the channel impulse response of this sector, as in the program

17,Step 300.

[0122] Eight=(ckD*cscram*D) Oh® program 17

[0123] c is the first?¹¹The strictest section of the code. csc ram% is the strictest section of the scrambling code. h^(k)It is the channel response of the first resource unit. Therefore, the length of each column of the km-th resource unit is Qk+Lr-1.

[0124] The column blocks of the resource unit system response matrices A1 to Ak are used to generate the support blocks of the symbol order matrix of FIG. 13. Figure 15 illustrates a support block BW of a Ph resource unit in the first symbol block. The support block has the column Qmax/Qro as an illustration, if the maximum expansion factor of the system is 16 (Qq= and the resource unit The expansion factor of is Qk =1, and the supporting block has 16 columns. Conversely, if the resource unit expansion factor is 16, the supporting block B%) has 1 column.

[0125] is from one k^thThe first supporting block of the resource unit, the resource unit system response matrix A_kThe first row of blocks Qmax/Qr is obtained. The first column of the support block has the first block column of the system response matrix K. The upper part of the first block row in the supporting block is located on the upper part of the supporting block. The overall height of the generated support block is QMAx+Lr-1, regardless of the expansion factor Qk, step 302.

[0126] FIG. 13 shows the symbol sub-matrix B^(a'^k)Support block in the. Each symbol sub-matrix has one s for each resource unit^thSupport block B^(s'^k),Step 304. Or, column b^(k' ^υAvailable from A_kGet the matrix or directly insert the sub-matrix B of the symbol element^(s'^k\ Each block column of the support block b^(k'ⁿIt is obtained from a block column of the Ak matrix of the resource unit. The column of the matrix from the one-symbol sub-block is b^(k'^x+1)Only add to the elbow dish. X comes from program 18.

[0127] X = (sD^x/Q, program 18

[0128] It is a specific resource unit k, and each block includes the Q/U of the resource unit column block. The upper part of the first row in the support block is on the upper part of the support block. Each subsequent column is the lower Qmax/U chip in the support block.

[0129] As shown in FIG. 13, each symbol sub-block has a supporting block B&amp;J for each resource unit, although the resource units can be set in any order and still achieve a reduced bandwidth. The resource unit of the expansion factor transmission is outside each matrix block, and the bandwidth can be further reduced. For illustration, the block in the first column of the first support of the first matrix is Lr. If the expansion factor is 16 (Qi = 16), the length of the block in the first column is 15+Lr. These additional 15 chips increase the overall bandwidth. With the last column of the last support of the last matrix, this is still true. However, in some implementations, the potential reduction in bandwidth may not be more important than the increased complexity for rearranging the order of resource units.

[0130] The sub-matrix of the wide symbol element has a supporting block for each resource unit, step 304. Because each support block has the same height, each matrix has the same height of QMAx+Lr-1 chips, and the width of each matrix is M, as in procedure 19.

[0131] M = ^Q_MtVllQ_k Procedure 19

[0132] The first symbol sub-matrix is located in the upper left corner of the system response matrix A. Each subsequent matrix is along the side of the previous matrix and the Qmax chip is further reduced. The overall height of A matrix is Ns*Qqin+Lr-1, and the overall width is M*NS. As shown in Figure 13, the structure of the A matrix greatly reduces the bandwidth. In addition, the complexity of deriving this reduced bandwidth A matrix is small.

[0133] In an actual communication station, due to over-sampling and transmission or reception differences, the A matrix may include several sub-matrices. The receiver at the user equipment or at the base station can sample the received vector r at multiple chip rates, for example at two or four times the chip rate. In addition, you can use transmit or receive differences. For a system that uses oversampling and transmission/reception differences, the A matrix can be viewed as a matrix with each combination of samples from oversampling and from that difference.

Sub-matrix. To illustrate, a receiver can sample at twice the chip rate that generates even and odd samples. This receiver can also differ in two spatial antennas. Antenna 1 and Antenna 2 receive signals. Therefore, an even set is in antenna 2 and an odd set is in antenna 1, an odd set is in antenna 1, an even set is in antenna 2 and an odd set is in antenna 2. In this case, the received signal can be in the mode described in procedure 20.

for"

2 Procedure 20

[0134]

[0135] Sample.

[0136]

[0137]

[0138]

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Α (ι, ο) corresponds to antenna 1 and even samples. A(i,e) corresponds to antenna 1 and odd samples. A(2,e) corresponds to antenna 2 and even in the general case, where multiple chip rate sampling is used and η antenna is used, A can be formed by program 21.

Αλ α==Program 21 is to reduce the bandwidth of the A matrix, and each matrix has its bandwidth reduced by a technique to reduce the bandwidth.

When the A matrix is used in the data detection method, the reduced bandwidth of each matrix reduces the bandwidth of the A matrix.

[0139] Although the present invention has been illustrated using preferred embodiments, the changes within the scope of the present invention that have been pointed out in the scope of the following patent applications are obvious to those skilled in the art.

CN 1663160 Β