WO2004052036A1

WO2004052036A1 - A method and unit for multi-user interference cancellation

Info

Publication number: WO2004052036A1
Application number: PCT/CN2002/000859
Authority: WO
Inventors: Qian Dai; Ying Liu; Meng Zhao
Original assignee: Zte Corporation
Priority date: 2002-11-29
Filing date: 2002-11-29
Publication date: 2004-06-17
Also published as: SE0501186L; CN100409707C; NO20053188L; NO20053188D0; AU2002349470A1; SE527387C2; NO334966B1; CN1685750A

Abstract

The invention disclose a method and unit for multi-user interference cancellation, which method mostly include: the input baseband signal is de-multiplexed and spreaded spectrum utilizing de-spread unit; then the de-spread signal proceeds to be de-spread with Walsh in different channel, so that the signal of each channel for user is separated; the separated bit stream of each channel multiplies a conjugate signal of the output estimated value from a pilot estimator A to counteract the effect in multipath fading; the multiplied bit stream is input to the decision circuit for judging; the steps for the constructing the threshold of judging as required etc.; utilizing other two pilot estimators B, C as well as the number of subscriber, the type of channel and the type of server providing by the system, the invention can control and process the signal decision and signal restore more accurately, increasing accuracy that interference is cancelled thereby improving performance of the system.

Description

Method and unit for eliminating multi-user interference

The present invention relates to multi-user detection in a code division multiple access communication system, and more particularly, to a multi-user interference cancellation method and unit. Background technique

Code division multiple access (CDMA) is one of the multiple access modulation techniques commonly used in mobile communications. Other multiple access modulation technologies include time division multiple access (TDMA) and frequency division multiple access (FDMA). Compared with other multiple access modulation technologies, code division multiple access technology has the advantages of high frequency band utilization and large system capacity.

In a CDMA communication system, the user signals overlap in the time and frequency domains and are distinguished from each other only by a spreading code. If the spreading codes are completely orthogonal, the signal of each user can be completely recovered by using a correlator or a matched filter. However, in practical systems, users are not synchronized and signals of different users reach the receiver with different delays, so it is difficult to find a certain spreading code sequence so that all users' signals are in all possible relative delay ranges. Inner orthogonal. Because the spreading code set is not completely orthogonal, interference exists between different users in the channel and different multipaths of the same user, that is, multiple-access interference (or multi-user interference). Traditional receivers use a correlator (or matched filter) for demodulation. Interference between users cannot be removed during the correlation process. For a user, the signals of other users are all considered noise. Therefore, as the number of users in the system gradually increases, the interference between users also increases. When these interferences accumulate to a certain level and exceed the minimum signal-to-noise ratio required for system demodulation, the system cannot access more User. Therefore, the CDMA system belongs to an interference-limited system. To solve the interference limitation problem of CDMA system to some extent, it is necessary to reduce the influence of multi-user interference. In fact, unlike system thermal noise, multiple access interference (MAI) is theoretically estimable and reproducible. Therefore, it is possible to synthesize the useful information of each user. 釆 Use a certain signal processing method to reduce the multiple access interference in the received signal. This is the goal to be achieved by the multi-user detection technology. Effective multi-user detection technology can increase system capacity, increase system coverage radius, and alleviate the problem of CDMA interference limitation.

At the same time, interference cancellation (multi-user detection) technology can also effectively reduce Impact on system performance. Because the distance between the mobile station and the base station is different and is affected by the fading of the wireless channel, the signal power received by the base station for each mobile station will be different, and users with strong power signals will cause a lot of interference to users with weak power signals. The performance degradation of users with weak power signals may not even work properly. The use of power control can make the power of all mobile stations received by the base station approximately equal, and alleviate the "far and near effect" to a certain extent. However, power control also has some shortcomings, such as the need to occupy the channel to transfer power control information, control lag, performance related to mobile user rate, etc., and power control cannot solve the problem of multiple access interference limiting system capacity. The starting point of power control is to control the interference to an acceptable level. Unlike this, the use of interference cancellation technology is to remove the interference between users to the greatest extent, so that the cause of the "far and near effect" is fundamentally eliminated. Therefore, it can effectively mitigate the effects of "far and near effects" and reduce the system's performance requirements for power control.

Usually mobile communication is faced with a time-varying multipath fading environment. In such an environment, the transmission of the transmitted signal through different paths will reach the base station with different delays. Because the spreading codes are not completely orthogonal, there is also MAI-like mutual interference between different multipath signals of the same user. . In the traditional CDMA receiver design, the Rake branch is used to demodulate the strongest several-path signals of each user, and then the maximum ratio combining is performed. Diversity is used to overcome the effects of multipath fading. However, in the demodulation process of each path, other multipaths are still regarded as noise, and the information contained therein is not fully utilized. Therefore, in the environment of multipath propagation, simply performing diversity and receiving cannot provide the effect of simultaneously overcoming the effects of multiple access interference and multipath. If multi-path detection is considered in the multi-user detection algorithm, it is obvious that the effective information can be fully utilized, thereby further improving the system performance.

Multi-user detection receivers can be classified into linear multi-user receivers and non-linear multi-user receivers based on whether their structure has feedback.

The linear multi-user detector is equivalent to multiple access interference in a multi-user communication environment as a channel transmission response matrix, and the transmission matrix is related to the spreading sequence of each user and the relative delay between the sequences. If we can get the inverse matrix of the channel transmission matrix, we can pass the multi-user signal through the output of k (k is the number of users) matched filters, and then perform the inverse operation through this inverse matrix to eliminate the equivalent of each user. Correlation between them, so as to achieve the purpose of eliminating multiple access interference. However, since this method needs to know the precise phase information between the spreading codes, and also needs to calculate the inverse matrix of the correlation matrix at any time according to the change of the actual user or the environment, the algorithm is complicated, the amount of calculation is large, and it is not easy to implement in real time. Another important type of multi-user detector is called a non-linear multi-user detector (also called a subtractive interference cancellation detector). Its basic principle is to independently estimate the MAI information from each user at the receiving end, and then subtract some or all of the MAI of the corresponding user from the total received signal to obtain the interference-removed signal for each user, and then use it. Traditional receivers perform demodulation. Such a feedback-based detector is usually implemented in a multi-level manner, and it is expected that the maximum degree of interference cancellation is achieved through multi-level feedback, so as to obtain better demodulation performance. It can be seen from the analysis of the linear multi-user detector that matrix operations are mainly used in the linear multi-user detector, and the calculation is relatively complicated, which is not conducive to the implementation of the hardware. From an implementation perspective, a non-linear multi-user detector is more efficient.

Non-linear multi-user detectors can be implemented in a serial or parallel architecture. Detectors with a serial structure generally need to sort the power of the input signals. In order, interference cancellation is performed on the stronger users first, and then the signals after interference cancellation are used as input, and the weaker signals are processed the same. When the effect of power control is not obvious or there is a lag, the performance of serial processing is better than parallel processing, but it will introduce a processing delay proportional to the number of users; the power is balanced between users or the system requires processing delay When higher, a parallel structure is usually used. No matter which kind of structure is adopted, multi-stage processing is generally performed to obtain better interference cancellation effect.

Whether using a serial or parallel architecture, the performance of a multi-user detector is determined by the ICU (Interference Cancellation Unit). ICU usually includes two parts of signal decision and signal recovery. The goal of signal decision and signal recovery is to accurately reconstruct the data of each user at the receiving end, so that the interference of other users can be removed when the interference is eliminated, and at the same time, it is necessary to ensure that additional interference is not introduced due to signal reconstruction errors during the interference cancellation process. interference. The accuracy of signal decision and signal recovery will directly affect the signal reconstruction capability of the ICU, and thus determine the performance of the entire detector. Therefore, how to accurately perform signal decision and signal recovery has become a key factor to improve the performance of the detector.

The current research on multi-order interference cancellation can be roughly divided into two categories: non-decision interference cancellation and decision interference cancellation (also known as soft decision interference cancellation and hard decision interference cancellation). Non-decision interference cancellation directly uses the output of the relevant receiver to generate an interference recovery signal, and no channel parameters need to be estimated during processing. Its algorithm is relatively simple, and the gain of interference cancellation can be obtained in a white noise channel; however, if the influence of multipath fading is not considered in a Rayleigh channel, the signal obtained without RAKE processing cannot overcome the influence of fading, and the interference is recovered. If there is not much reconstruction after passing through the channel, Signal, the recovered signal thus obtained will be significantly different from the actual received signal. After the interference is eliminated, interference is likely to be introduced, which directly leads to the performance degradation of the system in the Rayleigh environment. Decision interference cancellation uses the combined signals of RAKE for judgment, and multipath signals are restored during reconstruction, which can effectively remove multi-user interference and multipath interference. NEC's patent 6081516, "Multiuser Receiving Device For Use In A CDMA System"("Multiuser Receiver For Use In A CDMA System"), first performs a hard decision on the RAKE combined data, and then uses path estimation to recover multiple Signal, and then perform interference cancellation, suitable for Rayleigh fading environment. However, because the corresponding characteristics of the received signal are not processed during the judgment, when the amplitude of the received signal of a certain user or a certain path is small, the reliability of using this signal for judgment and recovery is relatively low. In this case, because The interference recovery signal is inaccurate and will instead introduce interference during the interference cancellation process.

The paper "Third Generation Mobile Radio Systems Using Wideband CDMA Technology and Interference Canceller for Its Base Station" (JE FUJITSU Sci. Tech.J., 34, l, pp. 50-57 (September 1998)), that is, "Using Broadband CDMA Technology The third-generation wireless mobile system and interference cancellation at the base station side adopt some techniques to improve the accuracy of signal decision and signal recovery. First, a mixed decision is used in the signal decision. Specifically, a threshold is set according to the energy of the path estimation. If the signal energy after the RAKE combination is larger than the threshold, the decision is +1 or -1; Threshold normalized (less than 1) value. It can be understood that when it is greater than the threshold, the reliability of the received signal is high, and the judgment can be considered accurate; but when it is less than the threshold, the reliability of the received signal is poor, and it is very likely to be misjudged, even if the judgment is a relative amplitude If the value is smaller, the interference will still be enhanced when the interference is eliminated. In this way, in multi-stage processing, the accumulation of errors will cause a rapid decline in performance.

Paper "Successful Interference Cancellation for Multiuser Asynchronous DS / CDMA Detectors in Multipath Fading Links" (see IEEE TRANSACTIONS ON COMMUNICATIONS, VOL.46, NO.3, MARCH 1998), § "Asynchronous DS / CDMA in Multipath Fading Environments" Receiver serial interference cancellation technology "also uses the threshold decision algorithm. Unlike the previous paper, no decision is made when the combined signal energy is less than the threshold. In addition, the calculation of the threshold in this paper is calculated according to the received signal energy variance of the user to be demodulated, the interference user energy variance, and the noise energy variance. However, in practical systems, the accuracy of these three energy variances must be obtained. Determining the value is not a simple process, and if the thresholds of the three parameters are to be calculated according to changes in the environment, more complicated calculations are required. Summary of the invention

The purpose of the present invention is to propose a multi-user interference cancellation method and unit in view of the defects of inaccurate signal decision and signal recovery in the existing interference cancellation unit.

In order to achieve the foregoing objective, the present invention adopts the following technical solutions,

The method for canceling multi-user interference according to the present invention includes the following steps: a. Perform de-complex spread-spectrum operation on an input baseband signal by using a de-spreading unit;

b, and then the channel-spreading Walsh despreading is continued on the despread signal to separate the signals of each channel of the user;

c multiply the bit streams of the separated channels by the conjugate signal of the output estimation value of a pilot estimator A to cancel the influence of multipath fading;

d, the multiplied bit stream is sent to a judger for judgment;

e. Use the other two pilot estimators 8, C and the number of users, channel type, and service type provided by the system to construct the threshold required for the decision, and then judge the input bitstream to be determined;

f. Multiply the determined bit stream with the estimated value output by pilot estimator A to reconstruct the effect of multipath fading and subsequent reconstruction of the signal.

In the step d, when making a judgment, the method further includes the following steps:

dl, obtaining parameters such as the number of users and channel type or service type from the system;

02, determining channel type or service type information;

d3. Adjust the coefficient K2 in the formula ^ ^ H H according to the information in step d2;

d4, judging the current number of users;

d5. Adjust the coefficient K1 in the formula of step d3 according to the number of users.

In the step d3, when the coefficient K2 is adjusted, the higher the channel rate is, the higher the value of K2 is, and the K2 corresponding to the convolutional coding channel is larger than that of the turbo coding type channel.

When adjusting the coefficient, first determine K2, and then determine K1. The value of κ2 increases as the channel rate increases. The change of the height and coding type increases approximately linearly. In specific operations, K1 can be temporarily set to about 1 to 3, and then the optimal value of K2 under different channel rates and different coding modes can be simulated and tested.

In the step e, the decision may be made with a double threshold decision, that is, when the energy of the bit to be decided is less than the threshold 1 (T1), the decision is 0; otherwise, when the energy of the bit to be decided is greater than the threshold 2 (T2), It is also judged to be 0; otherwise it is judged to be 1 or 1. In the step d3, it can also be adjusted according to the formula ^^ W mm ^-^, where K3 is a confidence factor and a number not less than 1.

When making adjustments,

First obtain the output signal of the pilot estimator C, and then according to the formula Energy [PilotChip _k ]

E C =

_ k

And formula

Bas = b E_ C

Calculate E-B's measurement basis Bas, determine whether E-B is greater than Bas, if it is greater, it means that the bit energy is stronger, then reduce K3;

Then judge whether K3 has decreased to a value less than 1, and if it is less than 1, let K3 = l _; if E-B is less than Bas, indicating that the bit energy is weak, then keep or increase K3;

Then determine whether K3 exceeds the maximum value MAX-K3, where ΜAX_Κ3 is an integer greater than 1.

The multi-user interference cancellation unit of the present invention includes a despreading unit, three pilot estimators, eight, B, C, a first multiplier, a multiplexer, a decider, and a second multiplier, and the despreading unit performs a solution on the input signal. The user signal is separated from the total signal, and the despread signal is sent to three pilot estimators on the one hand, and the despread bit stream is sent to the first multiplier. The output signal of the frequency estimator A is conjugated by the conjugate, and the first multiplier multiplies the despread bit stream and the signal after the conjugate of the conjugate; the decider uses the outputs of the pilot estimators 8, C The signal and system information are used to make a decision on the bitstream to be determined output from the first multiplier; the second multiplier multiplies the output signal of the decider and the signal output from the pilot estimator A again. Adjust the input of the module. Overview of the drawings

Figure 1 is a schematic block diagram of a conventional receiver.

FIG. 2 is a schematic diagram of a conventional multi-user detection parallel interference cancellation structure.

FIG. 3 is a schematic structural diagram of an interference cancellation unit according to the present invention.

FIG. 4 is a schematic flowchart of an interference cancellation method according to the present invention.

FIG. 5 is a schematic diagram of the interference cancellation method (changing a decision threshold according to different situations) according to the present invention. 6 is a schematic diagram of a demodulation performance curve of a receiver under different decision thresholds after using the method of the present invention.

FIG. 7 is a schematic diagram of a decision process (how to reduce a decision error rate) in the interference cancellation method of the present invention. FIG. 8 is a schematic diagram of a decision (how to measure the confidence of the decision) in the interference cancellation method of the present invention. Best Mode of the Invention

Figure 1 illustrates the basic principle of the receiver. The RF module converts the received RF signal into a baseband signal and sends it to the demodulation module for demodulation. The demodulated symbol stream is sent to the decoder for decoding. Generally, an RF processor includes a mixer and a local oscillator, which can convert an RF signal into an intermediate frequency signal and then further convert it into a baseband signal.

The demodulation module includes a RAKE receiving module to search for the strongest k multipath signals; a despreading module uses the mixed PN spreading sequence corresponding to each user to despread each path signal of each user; finally, The despread symbol stream is multiplied with Walsh function sequences corresponding to different channels, and the obtained bit stream can be sent to a decoder for decoding.

The decoder selects the corresponding decoding method according to different encoding methods of the signal, for example: Fundamental channel uses a convolutional encoding method, and the corresponding decoding method is Viterbi

(Viterbi) decoding; and when the Supplemental channel uses Turbo encoding, the corresponding decoding method is Turbo decoding.

FIG. 2 illustrates a conventional multi-user detection parallel interference cancellation (PIC: Parallel Interference Canceller) cancellation structure. The structure includes M-stage multi-user detection processing (M> 1), and each stage includes N ICUs, where N is the number of users. The N ICUs are arranged in parallel to perform interference cancellation at the same time, instead of first selecting the strongest user for interference cancellation like serial interference cancellation. Every The delay length of the first-order delay units 201-1 to 201-M is equal to the processing delay of the corresponding order, so as to ensure that the two input signals of the subtractor 204-n (n is 1 ~ -M) are synchronized.

It is worth noting that the interference cancellation structures of the first and last orders are slightly different compared to the other orders. The input signal of the first stage is taken from the output of the matched filter 206, while the input signals of the other stages are the outputs of the subtractor of the previous stage, that is, the signal after interference cancellation. The last-order ICU 2-M-1 to 2-M-N only need to perform interference signal reconstruction. After the multi-user detection of all stages is over, the final output signal An is the interference reconstructed signal (n is 1 ~ -N) by subtracting and removing interference from all users except user n. In theory, if the signals of all users can be accurately reconstructed, even in the case of multiple users, the demodulation performance is the same as that of one user.

Please refer to FIG. 3 first, which is a schematic structural diagram of an interference cancellation unit (ICU) in FIG. 2, that is, a structure of an interference cancellation unit used in the present invention. This unit includes a despreading unit, three pilot estimators A, B, and C, a first multiplier, a conjugate, a decider, and a second multiplier. The despreading unit despreads an input signal, which is useful for users. The signal is separated from the total signal, and the despread signal is sent to three pilot estimators on the one hand, and the despread bit stream is sent to the first multiplier, and the output of pilot estimator A is The signal is conjugated by a conjugate, and the first multiplier multiplies the despread bit stream and the conjugated signal; the decider uses the output signals of the pilot estimators 8, C and the system information to A to-be-determined bit stream output by a multiplier makes a decision; the second multiplier multiplies the output signal of the decider and the signal output from the pilot estimator A again, and the result of the multiplication is the input of the demodulation module in the subsequent stage.

The traditional ICU structure has only one pilot estimator, and the signal of the pilot estimator is used for weighting the despread signal and reconstructing the received signal, and it is also used as a reference signal for the decider. However, since the weight of the despread signals and the reconstruction of the received signals are essentially to cancel and reconstruct the multipath fading effects in the received signals, this requires that the cumulative length of the pilot estimator should not be too long and the delay should not be too large. The pilot estimation can only contain sufficiently accurate multipath fading components; however, such pilot estimation is not suitable for use as a reference signal for a decision device. Therefore, dedicated pilot estimators B and C are added to the ICU structure provided by the present invention, which are used as reference signals for the decider, and the pilot estimator A is dedicated to weighting the despread signals and reconstructing the received signals.

FIG. 4 is a flowchart of an interference cancellation method of the present invention. The method of the present invention is as follows. The input signal is despread in response to the user's mixed PN spreading sequence, the user's useful signal is separated from the total signal, and the despread signal is sent to the pilot estimator A-C. In the second step 402, the PN despread signal is further subjected to channelized Walsh despreading, and the signals of each channel of the user are separated. Steps 401 and 402 are performed in the despreading unit. Steps 404, 408, and 410 respectively extract pilot estimates A, B, and C according to different pilot estimation methods. In step 412, the bit streams of the separated channels are multiplied by the conjugate signal of the output signal of the pilot estimator A to cancel the influence of multipath fading, and the multiplied bit streams are sent to a decision device for judgment. Step 416 uses the pilot information 8, C, and the system information provided in step 414 to construct the threshold required for the decision, and then judges the input bitstream to be determined. In step 418, the determined bit stream is multiplied with the pilot estimate A to reconstruct the influence of multipath fading, and then the subsequent reconstruction process of the signal, including Walsh spreading, mixed PN sequence spreading, etc., will not be described in detail. . The outputs of the pilot estimator B and pilot estimator C and the system information of FIG. 3 are inputs required by the decider to make a decision. The detailed functions will be described below.

The role of the decider is to decide the input bit stream into a sequence of ones and ones. The simplest decision method is: if the amplitude of a bit is greater than 0 level, it is judged as 1; otherwise it is judged as -1. Considering the effects of thermal noise and multipath fading, this decision method is obviously very imprecise. In order to make a more accurate decision and to avoid introducing additional interference as much as possible, it is necessary to introduce a threshold for the decision process. The new judgment method is: if the amplitude of a bit is greater than the threshold, it is judged as 1; if the amplitude is less than the negative threshold, then it is judged as -1; otherwise it is judged as 0 level. This method takes into account that when the bit amplitude is weak, the decision credibility of the bit is relatively low. Instead of judging it to a non-zero value, it is better to judge it to 0 to avoid introducing possible additional interference. In addition: due to the large fluctuation of the bitstream energy caused by multipath fading, obviously using a fixed decision threshold will not bring accurate decision results, and because the size of the bit energy is difficult to predict, it is difficult to specify the fixed threshold Realized. Considering the above factors, the threshold value used in the present invention can be obtained by the following formula:

Threshold = K \-K2-E _ B ₍₁₎ where EJ3 is the energy value of the output signal of pilot estimator B, K1 depends on the number of users, K2 depends on the channel type or service type of the corresponding user, K1 and K2 are both Is non-negative. For example: If the user uses a supplementary channel of 153.6kbps, its K2 is greater than the basic channel of 9.6kbps. Both K1 and K2 need to be obtained through simulation and real-field testing. Figure 6 shows the number of different users in the simulation. With the same demodulation performance curve under the decision threshold, the channel used is a basic channel at 9.6 kbps. It can be found from this that: when the number of users is different, the optimal decision threshold is also different. In other words, K1 changes with the number of users. The best K1 and K2 must be summarized based on a large amount of simulation data and real-field test data.

FIG. 5 is a schematic diagram of the interference cancellation method (changing a decision threshold according to different situations) according to the present invention. The process is as follows: the first step 502 is to obtain parameters such as the number of users and channel type or service type from the system, and these parameters are easily obtained; the second step 503 determines what the channel type or service type is, such as a basic channel or a supplement Channel, what is the channel rate, what is the encoding type, etc. The third step 504 adjusts the coefficient K2 according to the information of the second step 503, for example: the higher the channel rate, the higher the value of K2; the K2 corresponding to the convolutional coding channel should be larger than the channel of the turbo coding type. Generally speaking, the value of K2 increases approximately linearly with the increase of the channel rate and the type of coding (convolutional coding to turbo coding). In specific operations, K1 can be temporarily set to about 2 to 3, and then Simulate and test the optimal value of K2 under different channel rates and different coding methods. The optimal value has little to do with the number of users, so the number of users during testing can range from 10 to 40. After K2 is determined, the fourth step 505 determines the current number of users, and the fifth step 506 adjusts K1 according to the number of users. For example: Referring to FIG. 6, when the number of users is between 10 and 20, the optimal K1 is 1; when the number of users is 30, the optimal K1 is 2; when the number of users is 40, the optimal K1 is 4 or 5, K1's value range is easy to determine through simulation, too large or too small is not good. Figure 6 is just the simulation results in a specific environment. To obtain the best Kl for various environments, a large number of simulation and real-field tests are required. Under different communication environments, the optimal value of K1 will be offset, but the offset will not be large. Therefore, an equilibrium point can be selected among these optimal values so that it can basically take into account various communication environments. Such an equilibrium point is the best K1 value for the current number of users. In specific implementation, a table of K1 and K2 can be made based on the test data, and the system can find the corresponding K1 and K2 according to the real-time system information (number of users, channel type, encoding type and other parameters).

E-B in the above formula (1) uses the energy value of the pilot estimator B. There is only one pilot estimator A in the traditional ICU. Because the pilot estimator weights the bit stream before and after the decision to offset and reconstruct the influence of multipath fading, the delay of the pilot estimator should not be too long. The cumulative length must not be too large, but the variance of the signal output by such a pilot estimator is necessarily large, and the energy The fluctuation is also severe, and it is not suitable for generating the decision threshold. Therefore, the pilot estimator B needs to be added to complete this work. The difference between pilot estimator B and pilot estimator A is that the cumulative length of pilot estimator B is long, so the variance of its output signal is small, the energy fluctuation is small, and the envelope of its energy is basically consistent with the bits to be determined. The energy envelope of the stream is more suitable for generating a decision threshold. It can be known from simulation experiments that compared with using pilot estimators A and B in combination with pilot estimator A, the demodulation effect after using pilot estimator B to generate a decision threshold is significantly improved.

At the time of judgment, if the bit energy is weak, it means that the credibility of the judgment is low. Similarly, if the bit energy is very strong and exceeds a certain limit, the energy should be regarded as an abnormality caused by interference. Energy, it is clear that the decision credibility of this bit is also low. Based on this point of view, in order to further reduce the additional interference brought by the decision error, the present invention uses a double threshold decision. That is, when the energy of the bit to be judged is less than the threshold value 1, or the energy of the bit is greater than the threshold value 2, the bit should be judged to be 0; otherwise, the bit is judged to be 1 or -1. Threshold 2 can be obtained by adding a factor to threshold 1. For example:

71 = ^ 1,-ΛΓ2, E_B ( ₂ ) T2 = a-T \ (3)

Among them, a is a number greater than 1, and the optimal value of a can be obtained through simulation and real-field testing (when a is infinity, it is equivalent to only the decision threshold T1). FIG. 7 is a decision process based on a double threshold. The decision principle is as described above, that is, when the energy of the bit to be decided is less than T1, the decision is 0 _; otherwise, when the energy of the bit to be decided is greater than T2, it is also judged to be 0; The double threshold decision can more effectively reduce the errors in the decision process, avoid the accumulation of errors in the multi-stage processing, and reduce the introduction of additional interference.

In a code division multiple access communication system, the reverse pilot channel is modulated and transmitted together with the traffic channel, and the air channel fading experienced is the same. Therefore, the shapes of the energy envelopes of the pilot channel and the traffic channel are basically the same. When the energy of the traffic channel becomes stronger, the energy of the pilot channel becomes stronger. Then, it can be thought from this that, because the decision threshold of the above method is generated by using the signal of the pilot estimator, the envelope shape of the decision threshold is also basically the same as the energy envelope shape of the traffic channel. In other words, the decision threshold is The envelope shape and the energy envelope shape of the bitstream to be decided are basically the same. In this case, when the bitstream energy is strong, because the decision threshold also increases, the bitstream is judged at this time. The probability of being 0 will also be greater. According to the foregoing statement, when the energy of the bit to be judged is strong, the credibility of its decision is high; otherwise, the credibility of its decision is low. Considering that the energy change of the bit stream is continuously gradual, so the following ideas are considered: when the bit stream energy is strong, the probability of bits being judged to be reduced is reduced, and when the bit stream energy is weak, Then the probability that the bit is judged to be 0 is maintained or even increased. This can further improve the accuracy of the decision.

In order to achieve the above viewpoint, a confidence factor may be added to the decision threshold. In structure, a pilot estimator C may be added in the interference cancellation unit. The output of the pilot estimator C is a long-term average of the energy of the pilot channel, and is used to measure the strength of the output energy of the pilot estimator B. The implementation structure of pilot estimator C is different from pilot estimators A and B, and can be expressed by the following formula −

Energy [PilotChip _k ]

E C = ^

-k (4) is the long-term average of the energy of the pilot channel since the channel was established. The long-term average value is used because it is relatively stable, and is less affected by multipath fading, and the energy fluctuation is also small, so it is more suitable as a reference for measuring the output signal of the pilot estimator B. The benchmark of measurement is obtained by:

Bas = b. E-C (5) where b is a factor less than 1 and greater than 0, and its optimal value needs to be obtained through simulation and real-domain testing; E-C is the output value of the pilot estimator C.

Therefore, the formula (1) of the decision threshold can be updated as:

Threshold = Kl-K2-K3-E _ B ( ₆ ) where K3 is the confidence factor and is a number not less than 1. The adjustment process is shown in Figure 8: First, the output signal of pilot estimator C is obtained, and then according to the formula ( 4) Calculate the benchmark Bas for E_B, and determine whether E-B is greater than Bas. If it is greater, indicating that the bit energy is stronger, then lower K3, which is equivalent to lowering the decision threshold and reducing the probability that the bitstream to be judged is judged to be 0. Then judge whether κ3 has decreased to a value less than 1, and if it is less than 1, let K3 = l; if E-B is less than Bas, indicating that the bit energy is weak, then keep or increase K3, which is equivalent to increasing the decision threshold and increasing In order to determine the probability that the bitstream to be judged is 0, and then determine whether κ3 exceeds the maximum value MAX- κ3, then let

K3 = ΜAX—K3. Wherein ΜAX_Κ3 is an integer greater than 1, the specific value can be obtained through simulation and Real domain test is determined.

In the entire interference cancellation technology, whether the useful signal of each user can be accurately reconstructed is the key to the effectiveness of the interference cancellation technology, and whether the despread bitstream in the ICU can be accurately judged is whether the useful signal can be accurately reconstructed. basis. The invention proposes a series of methods around how to reduce the error rate of the decision. Compared with other interference cancellation technologies, these methods are effective and easy to implement, the required input information is also easy to obtain, and the demodulation performance of the receiver is improved. It is more obvious, which is conducive to increasing system capacity and system coverage radius. ·

The interference cancellation method and unit of the present invention are mainly applied to a receiver having a multi-user detector, so that the demodulation performance and capacity of the base station can be improved.

The cancellation method and the cancellation unit provided by the present invention are not only applicable to a parallel interference cancellation structure, but also to a serial interference cancellation structure, and do not require much change. The present invention can also be applied to other digital communication systems or analog communication systems after appropriate modifications, as long as the mobile stations of the system also transmit pilot channels and conform to the IS-665 standard. Industrial applicability

Because the present invention adopts the above technical solution, compared with the prior art, it overcomes that when the value is less than the threshold, the reliability of the received signal is poor, it is very likely to be misjudged and misjudged, and the error accumulation during multi-level processing Will cause the disadvantage of rapid decline in performance. The invention performs more accurate control and processing on signal decision and signal recovery, increases the accuracy of interference cancellation, thereby improving the performance of the system; further increases the system capacity and mitigates the effect of "far and near effects" on system performance; The receiver behind the multi-user detector formed by the interference cancellation unit of the present invention can improve the demodulation performance and capacity of the base station.

Claims

Rights request

1. A method for canceling multi-user interference, which is characterized in that the method includes the following steps: a. Performing de-complex spread-spectrum operation on an input baseband signal by using a de-spreading unit;

d, the multiplied bit stream is sent to a decider for judgment;

2. The method for eliminating multi-user interference according to claim 1, wherein in step d, when performing a judgment, the method further comprises the following steps:

d2, determining channel type or service type information;

d3. Adjust the coefficient K2 in the formula ^^^^ ^ '^ ^^ according to the information in step d2;

d4, judging the current number of users;

3. The method for eliminating multi-user interference according to claim 2, characterized in that: in said step d3, when adjusting the coefficient K2, the higher the channel rate, the higher the value of K2, and the convolutional coding channel corresponds to K2 is larger than the channel of the turbo coding type.

4. The method for multi-user interference cancellation according to claim 3, characterized in that: when adjusting the coefficient, first determine K2, and then determine K1, and the value of K2 is presented as the channel rate increases and the coding type changes. Rising roughly linearly, you can temporarily set K1 to about 2 to 3 during specific operations, and then copy True sum tests the best value of K2 under different channel rates and different coding methods.

5. The method for canceling multi-user interference according to claim 2, characterized in that: in the step e, a double threshold decision is used when making a decision, that is, when the energy of the bit to be decided is less than the threshold value 1 (T1) , The judgment is 0; otherwise, when the energy of the bit to be judged is greater than the threshold 2 (T2), it is also judged as 0; otherwise, the judgment is 1 or 1.

6. The method for eliminating multi-user interference according to claim 2, characterized in that: in said step d3, it can also be adjusted according to the formula ^^-mm ^-, where K3 is a confidence factor and is not less than The number of 1.

7. The method for eliminating multi-user interference according to claim 6, wherein, when performing the adjustment,

E C = ^

One k

And formula

Bas = b-E _ C

Calculate the benchmark Bas of E_B, and judge whether E-B is greater than Bas. If it is greater, it indicates that the bit energy is stronger, then K3 is reduced;

Then judge whether K3 has decreased to a value less than 1, and if it is less than 1, let K3 = l; if Ε—Β is less than Bas, it means that the bit energy is weak, then keep or increase K3;

8. A multi-user interference cancellation unit, characterized in that the interference cancellation unit includes a despreading unit, three pilot estimators VIII, B, C, a first multiplier, a conjugate, a decider, and a second multiplication The despreading unit despreads the input signal, separates the user's useful signal from the total signal, and sends the despread signals to the three pilot estimators on the one hand, and the despread signals on the other. The bit stream is sent to the first multiplier, and the output signal of the pilot estimator A is conjugated by the conjugate. The first multiplier multiplies the despread bit stream and the signal after the conjugate of the conjugate; Use the output signals of the pilot estimators 8, C and system information to determine the bitstream to be determined output by the first multiplier; The multiplier multiplies the output signal of the decider and the signal output from the pilot estimator A again, and the result of the multiplication is the input of the demodulation module in the subsequent stage.