Method and equipment for radio communication

Technical field of method and equipment for wireless communication

[0001] The present invention generally relates to wireless communication systems. In particular, the present invention relates to the detection of multi-user signals in a wireless communication system.

[0002] Background of the invention

[0003] A typical wireless communication system includes base stations that communicate with wireless transmit/receive units (WTRUs). Each base station has a related operating area, which communicates with WTRUs in this operating area. In some communication systems, such as coded multi-directional proximity (CDMA) systems, the same frequency spectrum is used to transmit multiple communications. Such communications are usually distinguished by coding.

[0004] Since multiple communications can be transmitted at the same frequency spectrum and at the same time, a receiver in this system must distinguish these multiple communications. One solution for detecting these signals is matched filtering. In the matched filtering method, a communication transmitted with a single code is detected. Other communications are treated as interference. To detect multiple codes, a corresponding number of matched filters must be used. These signal detectors have low complexity, but suffer from multi-directional proximity interference (MAI) and inter-symbol interference (ISI).

[0005] Other signal detectors try to eliminate interference and ISI from other users, such as parallel interference cancellers (PICs) and continuous interference cancellers (SICs). These receivers tend to have better performance, at the expense of increased complexity. Other signal detectors jointly detect multiple communications, which is called joint detection. Some joint detectors use the Cholesky decomposition method for a minimum mean square error (MMSE) detection and forced zero block equalizers (ZF-BLEs). Such detectors tend to have better performance, but high complexity.

[0006] Therefore, it is desirable to have other multi-user detection solutions.

Summary of the invention

[0007] Receiving multiple signals in a shared spectrum. A received vector is generated from the samples of the received user signal. The received vector is divided into multiple sections. For each segment, continuously determine each user or signal group (signal group with similar received power) by determining a user/signal group and removing the component of the user/signal group from the received vector symbol. For example, the symbol of each user/signal group is determined by means of equalizing the channel and then despreading. Combine the determined symbols corresponding to each segment into a data vector.

Description of the drawings

[0008] FIG. 1 is a simplified diagram of an equalized continuous interference cancellation (EQ-SIC) receiver.

[0009] FIG. 2 is a diagram of a better segmentation method on a received vector.

[0010] FIG. 3 is a schematic diagram of an EQ-SIC device.

[0011] FIG. 4 is a flowchart of an EQ-SIC receiver.

Detailed ways

[0012] The preferred application of the preferred embodiment lies in the One Frequency Division Duplex (FDD) mode of the Third Generation Partnership Project (3GPP) Wide Band Code Multi-Directional Proximity (W-CDMA) communication system. However, the preferred embodiment can also be applied to many wireless communication systems.

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[0013] These preferred embodiments can be used in a wireless transmit/receive unit (WTRU) or a base station. A WTRU is not limited to include a user equipment, a mobile station, a fixed or mobile subscriber unit, a pager, or any other device type capable of operating in a wireless environment. A "base station" non-limiting includes a base station, a B-level node (Node-B), a network point controller, an access point, or other interface devices in a wireless environment. In addition, these preferred embodiments can be applied to WTRs that communicate with each other.

[0014] FIG. 1 is a schematic diagram of a preferred equalization/continuous interference cancellation (EQ-SIC) receiver. Preferably, most of the components shown in FIG. 1 except for the antenna 20 are implemented as a single integrated circuit. Alternatively, the individual components may be discrete components or a mixture of integrated circuits and/or discrete components.

[0015] Multiple communications are received by an antenna 20 or antenna array of the receiver. A sampling device 22 (such as single or multiple analog-to-digital converters (ADCs)) samples the received signal to generate a received vector.

[0016] The received vector is processed by a segmentation device 24 to generate a segment port on the received vector, -r_nOFigure 2 is a diagram of a better segmented architecture, but other architectures are also possible. As shown in Figure 2, the receiving vector is divided into multiple section ports,...© (shown only section ports, £2, top 3, top 4, top 5, £6, top 7, top 8 And Uzbekistan). Preferably, these sections overlap locally as shown in the figure. The amount of overlap is preferably twice the length of the impulse response minus one chip, that is, 2X (W-1)_OEven if the length of the section is limited, this overlap helps equalize all the chips. In the case of a known section, all the chips constituting the part of the section are equalized. For example, the part of the bird is bounded by a dashed line. The last chip in this section will extend to the next section by w-1 chips. Conversely, the farthest chip before the first chip extending into the area is W-1 chips before the first chip. Therefore, all the chips constituting the part and the chips not in the part can be equalized, effectively removing the components of the chips in the part.

[0017] Although the amount of overlap shown in the figure is roughly twice the impulse response, a larger amount of overlap can also be used. Depending on the actual receiver application, a larger amount of overlap may be advantageous. In one embodiment, the EQ-BIC device may use a prime factor algorithm (PFA) fast Fourier transform (FFT) type application. The amount of overlap can be extended to reach a desired optimal PFA or FFT length. In other applications, the best non-overlapping part can vary depending on the signal being processed. For example, in the time division duplex (TDD) mode of 3GPP W-CDMA, the length of the data field may vary depending on the burst type. Therefore, the optimal segment length of one burst data block may not be the best case for another burst data block. When a consistent hardware configuration is to be used, a predetermined segment size can be used. Different amounts of overlap can be used to promote different burst data block lengths.

[0018] A channel evaluation device 26 evaluates the channel response of each received user signal. Generally speaking, the channel response is evaluated using a reference signal (such as a amble or a midamble sequence), but other techniques can also be used. The estimated channel response is represented by a channel response matrix H in FIG. 1.

[0019] FIG. 3 is a diagram of a preferred EQ-SIC device 28 for a receive vector segment port. The EQ-SIC device 28 includes an equalization vector section port, known, ..., fine T configured to generate the spread-spectrum data vector s, respectively_n,s_i2, -,S_iKEqualizer 34_ρ34₂, -34_Ko EQ-SIC device 28 also includes a data vector s for de-expanding the spread spectrum_iPs_i2, -,s_iKAnd the despreaders 36ι, 362, ···36κ configured to generate soft symbols and configured to generate the hard symbol vector d from the corresponding soft symbols_iP d_i2, ···, d_iKHard decision device 381,382, -38_Ko EQ-SIC device 28 also includes a data vector s_iPs_i2,... Determine the corresponding user component r_n,r_i2,... interference structure device 4 0_Ρ40₂,... and a subtractor 42], 422,... to remove the corresponding user components from the respective corresponding vector sections, Jin,... In an application, all user signals are classified, for example, the received power of the signals is used for classification. For the user with the highest received power, the received vector segment is equalized by an equalizer 34| using the channel response related to the user (user 1) to generate a spread-spectrum data vector. The code used to use the user signal is determined by

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A despreader 36] generates soft symbols of the user data. A hard decision device 38] makes a hard decision on the users soft symbol to generate a hard symbol vector. Also, "using the measured hard symbol, the interference construction device 40] determines the user 1s position on the spread-spectrum data vector. The component port "subtracts the user 1 component from the section by a subtractor 42 to generate a new section with the user 1 component removed." In a similar manner, a second highest received power level is processed. Second user (user 2). The hard symbol d of user 2_i2An equalizer 342 and a despreader 36 that generate the spread-spectrum data vector 22₂And the hard decision device 382 detects it. Use an interference construction device 402 and a subtractor 42? to remove the component port 2 of the user 2's name i. This procedure is repeated K-1 times to generate a segment κτ that becomes the vector port, and the K-1 user components of the vector port are removed. For the Kth user, there is only a hard symbol d_iKUse to generate spread spectrum data vector s_iKAn equalizer 34K, a despreader 36_κAnd hard decision device 38_κdetermination.

[0020] If the EQ-SIC receiver is used in a base station, in general, the hard symbols from all user signals will be restored. However, in a WTRU, the WTRU EQ-SIC receiver may only have the signal of one target user. Therefore, the continuous processing for each user can be stopped after the hard symbol of the target user's signal has been restored.

[0021] Although the above is to detect the signal of each user independently, it is also possible to jointly restore the signals of multiple users. In this application, the received signal power is used to group users into groups. Continuous processing will be performed for each group in sequence. For example, the first group of data is detected and then the first group of data is eliminated from the receiving section, and then the second group is performed.

[0022] After the data of each user in a section has been measured, a section storage device 30 stores the data vector, for example. In order to reduce the storage size, it is best to delete the section to remove the non-target part and leave only the target section part. A sector recombination device 32 generates a data vector Q with data from all sectors. The vector is usually formed by serially combining the data of each user in each sector. For example, data d from user 1 in section 1_nData d with user 1 from section 2₁₂Serial combination.

[0023] FIG. 4 is a flowchart of an EQ-SIC receiver. At the beginning, a receiving vector is generated, step 50. Perform a channel assessment for all users, step 52. Segment the receiving vector into r_P-r_n,Step 54. Make each section processed, step 56. Determine a user with the highest received power for an i-th segment, step 58. Equalize the received vector with the user, step 60. Use the user's code to de-spread the obtained spread vector, step 62. A hard decision is made on the despreading data, step 64. Determine the user's component of the received vector, step 66, subtract the user's component from the received vector, step 68. Using the reduced code reception vector as the reception vector in the subsequent steps, repeat steps 60-68 and step 70 for the user with the second highest received power. Store the result of the section and repeat steps 58-70 and step 72 for each remaining section. Combine the stored sections into a data vector Q, step 74. The rate at which the channel evaluation is performed or updated may vary from application to application, because the update rate depends on the nature of the time variation of the wireless channel.

[0024] Preferably, the equalization operation of each stage of the EQ-SIC device 28 is performed by using FFT, but other methods may also be used. One possible way of implementation is as follows. Each receiving section can be regarded as a signal pattern according to Equation 1.

[0025] r; = Hs+n Equation 1

[0026] H is the channel response matrix. ϋ is the noise vector. The target is the spread spectrum data vector, which is the convolution of the spread code C of the user or group and the data vector Q of the user or group, as in Equation 2.

[0027] s = Cd equation 2

[0028] The two solutions for solving Equation 3 first use an equalization stage and then use a solution expansion stage. Equalize each received vector section, step 54. The first equalization scheme uses a minimum mean square error (MMSE) solution. MMSE of each expansion section

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The solution is based on Equation 4A.

[0029] = (ΗΛΚ+ο T) 7 dagger equation 4Α

[0030] That is, the noise variance, and j is the identity matrix of the extended matrix. (J¹¹It is a complex conjugate transpose operation or Hermetian operation. The forced return to zero (ZF) solution is based on Equation 4B.

[0031] "= (OM) "Equation 4B

[0032] Another option is to write Equation 4A or 4B as Equation 5.

[0033] = R/'HsVi equation 5

[0034] R corresponding to MMSE_sIt is defined in accordance with Equation 6A.

[0035] R_s = H_s^hHs+ o²Is equation 6A

[0036] Another option, the Iζ of ZF is based on Equation 6B.

[0037] R_s = H_s^hH_s Equation 6B

[0038] A preferred solution to equation 5 is to use a fast Fourier transform (FFT), such as equations 7 and 8, and another solution to equation 5 is the Cholesky decomposition method.

[0039] R_s = Λ D_z = (1/P)D_ZXAD_z Equation 7

[0040] R;¹ = Dj Λ"ιζ = (1/P)D_ZXA XD_Z Equation 8

[0041] Shi is a Z-point FFT matrix and human is a diagonal matrix, the latter has an R_sThe diagonal of an FFT of the first row of an approximate round determinant of the matrix. The approximate wheel ring determinant can be represented by any row of the Iζ matrix. It is better to use a complete row with the most elements.

<td>[0042]</td><td>In the frequency domain, the FFT solution is based on Equation 9.</td>

<td>[0043]</td><td>Μ Xinyi</td>

<td>[0044]</td><td>p_] ,2nkn where F&amp;) = work x (must'N where k = 0,1, -, Ρ-l equation 9 η=0,</td>

<td>[0045]</td><td>0 is the Kronecker product. Μ is the sampling rate. Μ = 1 is the chip rate sampling and Μ = 2 is the double chip rate sampling</td>

kind.

<td>[0046]</td><td>After the Fourier transform F@) of the spread spectrum data vector has been determined, an inverse Fourier transform method is adopted.</td>

Formula to determine the spread spectrum data vector ί_ο