RU2293447C2 - Mode of supression of multi-user interference and a block for such supression - Google Patents

Abstract

FIELD: the invention refers to radio technique particularly to multi-user detection in communication systems of plural access with code division of channels.

SUBSTANCE: the proposed mode has in essence the following stages: demultiplexing and squeezing of the input signal of the main diapason with using a block of pressure. Then the squeezed signal is pressed according to Walsh algorithm in various channels to divide the user's channels. A separate flow of the bits of each channel is multiplied on interfaced signal of the output evaluative value from the block A of control evaluation to eliminate influence of multi-beam dying down. The bits flow is introduced after multiplication into a solver to make decisions. They fulfill stages for definition of the step for making decision, use two other blocks B and C of control evaluation and also data about quantity of users, channel and service types, provided by the system. The invention may control more accurately the decision making according to the signal and restore the signal, and also work out these decisions.

EFFECT: increases accuracy of suppression of multi-user interference.

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Description

Technical field

The invention relates to multi-user detection in code division multiple access (CDMA) communication systems. More specifically, the invention relates to a method for suppressing multi-user interference and to a unit for such suppression.

State of the art

Code Division Multiple Access (CDMA) is one of the multiple access modulation technologies used in mobile communication systems. Other multiple access modulation technologies include time division multiple access (TDMA) and frequency division multiple access (FDMA). The advantages of CDMA technology over other modulation technologies for multiple access are in the application of the high-frequency range and in the higher throughput of the system.

In a CDMA communication system, each user's signals overlap in the time and in the frequency domain, and these signals differ only in range extension codes. If these range stretch codes are completely orthogonal to each other, each user's signals can be completely reconstructed using a correlator and a matched filter. However, in practice, there is no synchronization between users, and the signals from various users arrive at the receiver with different time delays, therefore, in reality, it is difficult to find the form of sequences of extension codes that can make the signals of all users orthogonal within all possible relative time delays. Since arrays of extension codes are not completely orthogonal, interference occurs between different users or between different beams of the same user, so-called multi-access interference (or multi-user interference). A traditional receiver performs signal demodulation using a correlator (or a matched filter), and during correlation there is no way to suppress interference between users. For a single user, all signals from other users are considered noise. Therefore, with an increase in the number of users in the system, the amount of interference between users is constantly growing. When the interference, folding, increases to a certain extent and exceeds the minimum signal-to-noise ratio (S / N) allowed by modulation in the system, this system can no longer provide service to an additional number of users. Therefore, a CDMA system is a jamming system. To solve the problem of interference limitation in a CDMA system, it is necessary to reduce the influence of multi-user interference. In essence, unlike thermal noise in a system, multiple access interference (PMD) can be theoretically estimated and reproduced. Therefore, it is possible to reduce PMD in the received signals by integrating the useful information of each user and using certain methods of signal processing, which is the task implemented in the technology of multi-user detection. Effective multi-user detection technology can increase the system throughput and its coverage radius and partially solve the problem of interference limitation in a CDMA system.

At the same time, interference suppression technology (multi-user detection) can effectively weaken the influence of the near-far effect on the functioning of the system. Due to the effect of fading in the wireless channels and the difference in distance between the base station and the mobile stations, the base station receives signals from different mobile stations with different powers. A user with a high signal power will impose a strong interference on the signals of a user with a low power, therefore, the quality of service of a user with a low signal power is reduced and even service failures are possible. Using power control technology can almost completely balance the power of all mobile stations, the signals from which the base station receives, and to some extent weaken the near-far effect. However, power control technologies also have some drawbacks, for example, the need to use a channel for transmitting power control data, control delay, the quality of service depending on the signal transmission speed of mobile communication users, etc. In addition, power control does not solve the problem of limiting system capacity due to PMD interference. Power management technology is only aimed at limiting interference to a certain acceptable level. In contrast to power control, noise reduction technology is used to eliminate interference between users as much as possible in order to radically eliminate the cause of the near-far effect. Therefore, interference suppression technology can effectively reduce the near-far effect and reduce the requirements for power control characteristics in the system.

Typically, mobile communications deals with a time-varying multipath environment with signal fading. In this environment, signals transmitted over various paths arrive at the base station with various time delays. Since the extension codes are not completely orthogonal, there are mutual interference between the signals of the same user transmitted on different paths, similar to PMD interference. In a traditional CDMA receiver, for the corresponding demodulation of signals arriving along several paths with the highest power for each user, the Rake channel is operated, after which the combination with the maximum ratio is used, as a result of which the influence of multipath fading is eliminated by applying the reception diversity method. However, when demodulating the signals of each path, the signals arriving on other paths are still considered noise, and the information contained in these signals cannot be used. Thus, in the conditions of multipath propagation, it is not possible to simultaneously solve the problems of multiple access interference and multipath effects by simply transmitting and combining diversity. If the multipath effect is taken into account in the multi-user detection algorithm, then it is obvious that it is possible to adequately use effective information and improve the characteristics of the system.

Receivers with multi-user detection can be divided into linear and non-linear multi-user receivers, depending on whether there is feedback in their structure.

A linear multi-user detector equates PMD interference in a multi-user environment with a transmission response matrix for a channel. The transfer matrix is associated with the extension sequence for each user and with the relative time delay between the extension sequences for different users. If a matrix is obtained that is inverse to the channel transmission matrix, then multi-user signals can be output through K matched filters (where K is the number of users), and the inversion operation using this matrix is implemented, so that the correlation between users can be equivalently suppressed and the PMD interference suppression problem can be solved . However, when using this method, it is necessary to know exactly the phase shift between the extension codes, and at each moment of change in the users being serviced or working conditions, calculate the matrix inverse to the corresponding transfer matrix. Therefore, the algorithm for using this method is complicated, the volume of calculations is large, and it is not so simple to ensure their implementation in real time.

Another important type of multi-user detector is called a non-linear multi-user detector (also a detector with subtractive noise reduction). According to the principle underlying this detector, the PMD information from each user is independently evaluated on the receiving side, then the PMD interference of the corresponding user is completely or partially subtracted from the total received signal to obtain each user's signal minus the interference, and then used to demodulate this signal traditional receiver. In essence, a multi-stage feedback detector is created, and it is assumed that due to the use of multi-stage feedback, interference is suppressed to the maximum extent to provide higher demodulation characteristics. Analyzing a linear multi-user detector, we can see that it uses a matrix operation with complex calculations, which does not simplify its hardware implementation. From an implementation point of view, a nonlinear multi-user detector is more efficient.

Non-linear multi-user detector can be implemented with a serial or parallel structure. A detector with a sequential structure usually requires first to rank the input signals by power, performs proper interference suppression for a user with a high signal power, receives a signal with eliminated interference as an input, and then performs the same processes for users with a lower signal power. In the case where the power control effect is not obvious or is delayed, the characteristics of the sequential process are higher than those for the parallel process, but there is a delay in the processing time in proportion to the number of users. If the power of the user signals is balanced relative to each other or if the system has increased requirements for the delay of the processing time, then a parallel structure is usually used. However, regardless of the type of structure in both of these structures, multi-stage processing is usually used to improve interference suppression.

Regardless of the type of structure used, serial or parallel, the quality of the multi-user detector is determined by the interference suppression unit (BPP). The BPP unit usually consists of two parts - the part of deciding on a signal and the part of signal recovery. The task of making a decision on the signal and restoring the signal is to accurately reconstruct the data of each user on the receiving side so as to suppress interference from other users in the process of suppressing interference and at the same time prevent the introduction of additional interference due to errors during reconstruction of the signal in the process of suppressing interference. The accuracy of decision making on the signal and signal recovery directly affects the ability of the BPP unit to reconstruct signals, which determines the general characteristics of the detector. Thus, the problem of accurately deciding on a signal and reconstructing a signal is critical to improving detector performance.

Currently, studies of multi-stage interference suppression are usually classified as belonging to the interference suppression category without a decision procedure and belonging to the interference suppression category with a decision procedure (also called soft and hard decision interference suppression). When suppressing interference without making a decision, the output of the correlation receiver is used directly to generate the reconstructed signal without interference, during which it is not necessary to estimate the channel parameters. This is a relatively simple algorithm, and it can improve noise suppression in the white noise channel. However, if you do not take into account the effect of multipath signal fading in the Rayleigh channel, the signal received without an end-to-end Rake process cannot overcome the effect of fading. In addition, when restoring interference, if the multipath signal transmitted through the channel is not reconstructed, then the recovered signal obtained during this process is very different from the actual received signal, which is likely to introduce distortion after suppressing interference and lead to degradation of system performance in the Rayleigh environment. Suppression of interference with decision making involves decision making when using a Rake-combined signal and restores the multipath signal in the reconstruction process so as to effectively suppress multiplayer and multipath interference. According to NEC Patent No. 6081516, entitled “Multiuser Receiving Device for Use in A CDMA System”, a hard decision is first made for Rake-combined data; restore the multipath signal using path estimation, and then suppress the interference, which is applicable to an environment with Rayleigh fading. However, since decision-making is carried out without an appropriate process based on the characteristics of the received signal, in the case of a decrease in the amplitude of the received signal from a particular user or in a specific way, the reliability of the implementation of decision-making and restoration using this signal becomes relatively low. In such a situation, since the reconstructed signal without interference is inaccurate, distortion is introduced in the process of suppressing interference.

The Third Generation Mobile Radio Systems Using Wideband CDMA Technology and Interference Canceller for Its Base Station document (see FUJITSU Science and Technology Journal, 34, 1, pp. 50-57, September 1998) describes some ways to improve reception accuracy signal solutions and signal recovery. First of all, when deciding on a signal, mixed decision making is used. In particular, a threshold is set depending on the estimate of the track power. If the power of the Rake-combined signal exceeds this threshold, then a value of +1 or -1 is accepted. If the power of the Rake-combined signal is lower than the threshold value, then the value (less than 1) normalized to the threshold is accepted. It is clear that the relative reliability of the received signal will be higher if the signal power exceeds a threshold value, in which case the decision can be considered accurate; however, if the signal power is below a threshold value, then the reliability of the received signal will be worse and, most likely, the decision will be erroneous. If the decision is made incorrectly, the interference during the suppression process, on the contrary, increases, even if the decision result has a relatively small amplitude value. As a result of the accumulation of errors, the characteristics in such a multi-stage process quickly deteriorate.

The document Successful Interference Cancellation for Multiuser Asynchronous DS / CDMA Detectors in Multipath Fading Links (see IEEE TRANSACTIONS ON COMMUNICATION, Volume 46, No. 3, March 1998) describes a threshold decision method. Unlike the previous document, decisions are not made here if the combined signal power is below the threshold. In addition, the threshold is calculated depending on the dispersion of the power of the signals received from users for demodulation, the dispersion of the power of the signals from users introducing interference, and the variance of the noise power. But in practice, it is not so easy to obtain the exact values of three power dispersions in a system. More complex calculations are needed to determine the threshold associated with three parameters depending on the change in the environment.

SUMMARY OF THE INVENTION

The aim of the present invention is to provide a method for suppressing multi-user interference and a block for such suppression, with which you can eliminate the disadvantages caused by inaccurate decision-making on the signal and signal recovery and occurring in the existing block of noise suppression.

To achieve the above objectives, the present invention provides the following technical solutions.

The proposed method of suppressing multi-user interference includes the following steps:

a) the implementation of the composite expansion for the input signal of the main range by using the compression unit;

b) implementing Walsh channel compression for the compressed signal to allocate user channels;

c) multiplying the bit streams of each individual channel by the conjugate signal of the output estimate value from block A of the check estimate to eliminate the effect of multipath fading;

d) sending the bit streams after they are multiplied into a decider for making a decision;

e) determining the threshold for decision making when using the other two blocks B and C of the control assessment and based on data on the number of users, types of channels and types of services provided by the system, and then making decisions on the input bit streams;

f) multiplying the bit streams for which the decision was made by the estimated output value from the control evaluation unit A to reconstruct the effect of multipath fading, and the subsequent reconstruction of the signal.

The above step "d" in the decision-making process includes:

d1) receiving from the system such parameters as the number of users and types of channels or types of services;

d2) defining information about channel types or service types;

d3) a change in the coefficient K2 in the equation Threshold = K1 · K2 · E_B, taking into account the information obtained in step d2;

d4) determining the number of users in the system at the moment;

d5) changing the coefficient K1 in the equation in step d3 taking into account the number of users.

At step d3, when the coefficient K2 changes, the higher the transmission speed of the channel, the higher the value of K2 must be taken. The value of K2 corresponding to the channel of the convolutional code must exceed the value corresponding to the channel with turbo-type encoding.

When changing the coefficients, first determine K2, and then K1. The value of K2 increases approximately linearly with an increase in the channel transmission rate and a change in the type of channel code. In practice, the value of K1 can be pre-set in the range of 2-3, and then simulate the optimal value of K2 and check it for various transmission speeds of the channels and various types of codes.

In step "e", at the time of making the decision, a decision can be made based on two thresholds. In particular, if the bit power by which a decision is to be made is less than threshold 1 (T1), then the value "0" is assumed; if the bit power by which a decision is to be made exceeds threshold 2 (T2), then the value "0" is also taken; in all other situations, take the value "1" or "-1".

At step d3, changes can also be made according to the equation Threshold = K1 · K2 · K3 · E_B, in which K3 is a confidence indicator with a value of at least 1.

When changing the values, first the output signal of the control evaluation unit C is received; then calculate the measuring base "Bas" for E_B according to the equation

and the equation Bas = b · E_C;

assessing whether E_B exceeds the value of 'Bas'; and, if so, this indicates that the bit power is higher and the value of K3 needs to be reduced; then evaluate whether the value of K3 is reduced to a value less than 1 and, if so, then take K3 = 1;

if E_B is less than 'Bas', then this indicates that the bit power is less and the value of K3 needs to be left unchanged or increased;

and then assess whether the value of K3 exceeded the maximum MAX_K3, and MAX_K3 - an integer greater than 1.

The proposed multi-user interference suppression unit includes a compression unit, three control evaluation units A, B and C, a first multiplier, a coupler, a resolver and a second multiplier. The compression unit compresses the input signal and extracts a useful user signal from the full signal. On the one hand, the compressed signal is sent to three blocks of the control evaluation, on the other hand, the compressed bit stream is sent to the first multiplier. The interface device transposes the output signal of block A of the control assessment. The first multiplier device multiplies the compressed bitstream by the signal transposed through the interface device. The decider uses the output signals of blocks B and C of the control assessment and the information received from the system to make a decision on the bitstream, according to which a decision should be made, leaving the first multiplier. The second multiplier device multiplies the signal produced by the deciding device by the signal at the output of block A of the control evaluation. The result of the multiplication is the input signal of the next stage of the demodulator module.

A brief description of the drawings.

Figure 1 depicts a simplified diagram of a known receiver.

Figure 2 depicts a simplified block diagram illustrating a known method of parallel interference suppression for multi-user detection.

Figure 3 depicts a simplified block diagram of the proposed block noise reduction.

Figure 4 depicts a diagram of the operations of the proposed method of suppressing interference.

Figure 5 depicts a simplified diagram of the proposed method for suppressing interference (changing the decision threshold depending on various situations).

6 depicts a graphical curve of the demodulation of the receiver at various decision thresholds according to the proposed method.

Fig.7 depicts a simplified diagram of a decision-making process (how to reduce the error rate when making decisions) according to the proposed method of suppressing interference.

Fig.8 depicts a simplified decision-making scheme (how to determine the reliability of the decision) according to the proposed method of suppressing interference.

Description of preferred embodiments of the invention

Figure 1 illustrates the basic principle of operation of the receiver. The radio frequency (RF) module converts the received radio frequency signal into a main band signal and sends this main band signal to a demodulator module for demodulation. The stream of characters after demodulation is sent to the decoder for decryption. Essentially, the RF signal processing apparatus includes a mixer and a local oscillator, which can convert the RF signal into an intermediate frequency signal, and then into a main signal.

The demodulator module contains a Rake-reception module for searching the K parts of the most powerful multipath signals; the compression module uses a hybrid PN extension sequence corresponding to each user to compress the signal along each path for each user; finally, the stream of compressed symbols is multiplied by the sequence of Walsh functions corresponding to each channel, and after that the bit stream obtained by multiplication is sent to the decoder for decoding.

The decoder selects the appropriate decoding mode depending on the different coding mode of the signals. For example, the main channel uses convolutional coding mode and its corresponding decoding mode - Viterbi decoding; at the same time, the additional channel uses the turbo coding mode, which corresponds to the turbo decoding mode.

Figure 2 shows a parallel interference suppression scheme (IFR) for conventional multi-user detection. The scheme includes a multi-user detection process, consisting of M steps (M> 1). Each step contains N BPP blocks, where N is the number of users. N BPP units operate in parallel processing mode and simultaneously suppress interference, in contrast to interference suppression in sequential mode, in which the user with the highest power signal is selected first to suppress interference. The delay duration of the delay blocks 201-1 - 201-M of each stage is equal to the time delay of the processing at the corresponding stage to ensure the synchronization of the two input signals of the subtractor 204-n (n = 1 ~ M).

It should be borne in mind that the noise suppression schemes of the first stage and the last stage are slightly different from similar schemes of other stages. The input signal of the first stage is taken from the output of the matched filter 206, and all input signals of other stages are taken from the output of the subtractor of the previous stage, i.e. these are signals with implemented noise reduction. Only the BPP 2-M-1 - 2-M-N blocks of the last stage should implement signal reconstruction without interference. After multi-user detection at all stages is completed, the resulting output signal An is a signal reconstructed from interference, obtained by subtracting all other users except user n from the full signal (n = 1 ~ N). Theoretically, if it is possible to accurately reconstruct the signals of all users, then the demodulation characteristics, even with many users, will be the same as if the user was alone.

Figure 3 depicts the structural diagram shown in figure 2 block BPP, namely, the proposed scheme BPP. The block includes a compression block, three blocks A, B and C of a control assessment, a first multiplier, a coupler, a resolver, and a second multiplier. The compression unit compresses the input signal and extracts a useful user signal from the full signal. On the one hand, a compressed signal is sent to three blocks of the control assessment; on the other hand, a compressed bitstream is sent to the first multiplier. The output of block A of the control assessment is transposed by the interface device; the first multiplier device multiplies the compressed bit stream by a signal transposed through the interface device; the decider uses the output signals of blocks B and C of the control evaluation and information obtained from the system to make a decision on the bit stream exiting the first multiplier. The second multiplying device multiplies the signal produced by the decision-making device by the signal at the output of block A of the control assessment. The result of the multiplication is the input signal of the next stage demodulator module.

In the traditional structure of the BPP, only one block of control assessment is used. The signal of the control evaluation unit is used not only for weighing the compressed signal and reconstruction of the received signal, but also as a reference signal for the resolver. However, the goal of weighing the compressed signal and restoring the received signal is to suppress and reconstruct the effect of multipath fading in the received signal, which requires that the control evaluation unit does not have too much cumulative duration and time delay so that it can sum up the multipath fading components accurately enough; but this type of control evaluation does not apply to the reference signal of the resolver. Thus, special control evaluation blocks B and C are added to the proposed BPP structure, designed to supply the reference signal of the deciding device, while control assessment block A is used specifically for weighing the compressed signal and reconstructing the received signal.

Figure 4 depicts a flowchart of the proposed method. According to the proposed method, at the first stage 401, the input signal is compressed using a hybrid PN extension sequence for the corresponding user, a useful user signal is extracted from the full signal, and then the compressed signal is sent to the control evaluation blocks A ~ C. In a second step 402, Walsh compression is performed for a PN-compressed signal to separate signals on each channel for each user. Steps 401 and 402 are performed in a compression unit. At steps 404, 408, and 410, control scores A, B, and C are retrieved depending on the different control score modes. At step 412, the bitstream of each individual channel is multiplied by the conjugate output signal of the control estimate block A to suppress the effects of multipath fading, and this multiplied bitstream is sent to a decision maker. At step 416, a decision threshold is created using the other two blocks B and C of the control assessment and system information provided at step 414, after which a decision is made on the input bit streams by which decisions should be made. At step 418, the decision bitstream is multiplied by a control score A to reconstruct the effect of multipath fading, and further signal reconstruction processes such as Walsh extension, extension by a hybrid PN sequence, which are not described in detail in this text, are performed. According to the proposed method, the system information and the output of the control evaluation blocks B and C are the input signals necessary for making decisions in a solving device, the operation of which is described in detail below.

The function of the solver is to determine the input bitstream as a sequence of values 1 and -1. The easiest way to make a decision is as follows: if the amplitude of a certain bit exceeds level 0, then the value 1 is taken, otherwise, the value -1 is accepted. This method of decision making is very inaccurate when you consider the effect of thermal noise and multipath fading. To ensure more accurate decision making and to the extent possible to prevent the introduction of additional interference, you need to set a threshold for the decision process. A new way of making a decision is that if the amplitude of an individual bit exceeds a threshold, then it is considered to be unit (1); if the amplitude is less than a negative threshold, a value of -1 is assumed; in all other cases, the value is 0. According to this method, it is assumed that the reliability of decision making for a bit is lower if its amplitude is less; in this case, it is better to accept a value of 0 rather than a non-zero value in order to prevent the possible introduction of additional interference. In addition, due to the widest variation in the power of the bit stream due to multipath fading, it is obvious that the use of a fixed decision threshold does not give an exact result for the decision. At the same time, bit power is difficult to predict, so it is really difficult to implement a fixed threshold. Given the above factors, the threshold value according to the present invention can be obtained from the following equation:

in which Е_В is the value of the output signal power of the control evaluation unit B, the value of K1 depends on the number of users, the value of K2 depends on the type of channel or on the type of service for the corresponding user, and K1 and K2 are non-negative numbers. For example, if the user uses an additional channel of 153.6 kbit / s, then for him the value of K2 is greater than for the main channel with a speed of 9.6 kbit / s. The values of K1 and K2 are obtained by emulation and field tests. Fig.6 depicts the performance characteristic of the quality of demodulation obtained by emulation at different decision thresholds for a different number of users, and the main channel with a speed of 9.6 kbit / s is used. The graph shows that the best decision threshold depends on the number of users. This means that after changing the number of users, the value of K1 changes. The optimal values of K1 and K2 can be selected based on an array of emulation data and field test data.

Figure 5 depicts a simplified diagram of the proposed method for suppressing interference (changing the decision threshold depending on various situations).

In this process, at the first stage 502, parameters such as the number of users and channel type or service type are obtained from the system, and obtaining these parameters is quite simple. In the second step 503, a channel type or a service type is determined, for example, the main one is a channel or an additional one, what is the channel transmission rate and what type of coding is used. In the third step 504, the coefficient K2 is changed based on the information obtained in step 503; for example, the higher the channel speed, the greater the value of K2. The value of K2 for the channel with convolutional type coding is higher than for the channel with turbo type coding. In the general case, the K2 value is characterized by an approximately linear increase with an increase in the transmission rate of the channel and a change in the type of code (change of a convolutional code to a turbo code). In practice, you can set a preliminary value of K1 in the range of 2-3, and then emulate and set the optimal value of K2 at various transmission speeds of the channels and various types of codes. Since the optimal value is not strongly related to the number of users, for testing you can take the number of users from 10 to 40. After the K2 value is determined, at the fourth step 505, the current number of users will be determined. In a fifth step 506, the value of K1 is changed depending on the number of users. For example (see Fig.6), when the number of users is 10-20, the optimal value of K1 is 1; for the number of users equal to 30, the optimal value of K1 is 2; for the number of users equal to 40, the optimal value of K1 is 4 or 5. The range of values of K1 is easily determined by emulation, and this value should be neither too large nor too small. 6 is a result of emulation only under special conditions. It is necessary to conduct many emulations and real field tests in order to obtain the optimal value of K1, determined by various conditions. Although the optimal value of K1 may be different under different communication conditions, the fluctuations of this value are not too large. This means that you can choose an equilibrium point from among the optimal values in order to generally fulfill the requirements imposed by various conditions. This equilibrium point is the optimal value of K1, selected depending on the number of users at the moment. In practical implementation, it is possible to compile, according to the test data, a table of values of K1 and K2, which the system can access when choosing the appropriate values of K1 and K2, depending on the actual data in the system (such parameters as the number of users, channel type, code type).

The value of E_B in the above equation (1) uses the value of the power of the control score B. The traditional block BPP contains only one block A of the control score. Since the control evaluation unit must weigh the bitstream before and after the decision is made in order to suppress and reconstruct the effect of multipath fading, the time delay and the total processing time of the control evaluation unit should not be too long. However, the fluctuations in the output signal of such a control evaluation unit are greater, and the power fluctuation is wider, which is not suitable for creating a decision threshold. Therefore, to perform this operation, you need to add a block In the control assessment. The difference between blocks B and A of the control evaluation is that the total processing time by the block B of the control evaluation is longer, therefore, the output signal fluctuations and power fluctuation are less. In addition, the power envelope of this block generally corresponds to the power envelope of the bit stream by which a decision should be made, therefore, the block is suitable for creating a decision threshold. According to the emulation tests, when comparing the result of using one block A of the control score with the result of sharing the blocks A and B of the control score, the demodulation result is improved if you use the block B of the control score to create a decision threshold.

If the bit power is lower when making a decision, then the reliability of the decision falls. According to the same principle, if the bit power is too high and exceeds certain limits, then the reliability of the decision on the bit obviously drops, since the power will be considered abnormal power due to interference. Based on the above statement, the present invention adopts a double decision threshold in order to further reduce the additional interference caused by an incorrect decision. According to the present invention, if the bit power by which a decision is to be made is less than threshold 1 or greater than threshold 2, the bit value is taken to be 0; in other situations, the value is 1 or -1. Threshold 2 can be obtained by adding a coefficient based on threshold 1, i.e.:

where a is a number greater than 1, and the optimal value of "a" can be obtained by emulation and real field tests (if we take the value of "a" equal to infinity, then this is equivalent to using only threshold 1).

7 illustrates a resolution algorithm using two thresholds. The principle of decision making is described above, i.e. if the bit power by which a decision is to be made is less than the value of T1, its value is taken equal to 0; otherwise, if the bit power by which a decision is to be made exceeds T2, its value is also taken to be 0. In all other cases, 1 or -1 is assumed. The double threshold method can effectively reduce the number of errors in the decision-making process, prevent the accumulation of errors during the multi-stage process and reduce the introduction of additional interference.

In a CDMA system, a reverse control channel operates along with the traffic channel. These channels are subject to the same signal fading characteristic of wireless channels, so that the shape of the envelope of the power of the control channel is generally similar to the shape of the envelope of the power of the traffic channel. With an increase in the power of the traffic channel, the power of the control channel also increases. Thus, it can be concluded that the shape of the envelope of the decision threshold is essentially the same as the shape of the envelope of the traffic channel, since the decision threshold, according to the method described above, is created using the signal of the control evaluation unit. In other words, the shape of the envelope of the decision threshold is essentially the same as the shape of the envelope of the power of the bitstream by which the decision should be made. Thus, the higher the power of the bitstream, the greater the decision threshold, so that the probability of a value of 0. is higher for the bitstream. According to the above description, if the power of the bitstream to be decided is high, then high and reliability of decision making on it; and vice versa, this confidence is lower at low bitstream power. Since the change in the power of the bit stream occurs continuously and gradually, it is possible to express the idea that during a period with a high power of a bit stream, it is necessary to reduce the probability of a zero (0) value for a bit, and during a period of a low power of a bit stream, the probability of a zero (0) value for a bit you need to leave it unchanged or even increase it. Thus, a further increase in the accuracy of the solution is provided.

According to the above statement, a confidence indicator can be added to the decision threshold. At the structure level, block C of the control assessment can be included in the BPP block. The output of the control estimate block C is the steady-state average value of the control channel power, which is used to measure the output power of the control estimate block B. The implementation of the structure of block C of the control assessment is different from the implementation of blocks A and B of the control assessment and is expressed as:

This is the steady-state average power of the control channel for the period from the moment the channel was established to the present. The reason for using the steady-state average value is that it is relatively stable and less dependent on multipath fading, the power fluctuation is also moderate, so this value is suitable for use as a reference value when measuring the output signal of block B of the control evaluation. The reference value for the measurements is obtained using the equation below.

where b is a coefficient less than 1 and greater than 0, and its optimal value is determined by emulation and real field tests. E_C is the output of the control score C.

Then equation (1) for determining the threshold can be changed as follows:

where K3 is a confidence indicator of at least 1, and the process of changing it is illustrated in Fig. 8. First you need to get the output of block C of the control assessment. Then calculate the measuring base "Bas" for EB_ according to equation (5). Then E_B is compared with "Bas". If E_B is greater than Bas, which indicates a high bit rate, then K3 must be reduced. A decrease in K3 is equivalent to a decrease in the decision threshold and is equivalent to a decrease in the probability of making a "0" value for the bitstream. When decreasing K3, it is necessary to check whether the coefficient K3 is reduced to a value less than 1. If K3 is less than 1, you need to take a value of 1. If E_B is less than "Bas", which indicates a low bit stream power, the value of K3 must be left unchanged or even to increase. An increase in the K3 value is equivalent to an increase in the decision threshold and is equivalent to an increase in the probability of making a "0" value for the bitstream. With an increase in K3, it is necessary to check whether the value of K3 has not exceeded the maximum value of MAX_K3. If so, you must accept the value K3 equal to MAX_K3. The value MAX_K3 is an integer greater than 1. This value can be determined by emulation and real field tests.

In general, in interference suppression technology, the accurate reconstruction of the useful signals of each user is a key factor for interference suppression, in which the exact decision on the compressed bit stream in the BPP unit is the basis for the accurate reconstruction of useful signals. With regard to reducing error rates in decision making, the present invention provides a number of methods. Compared with known solutions, the proposed methods are more effective and simple to implement. The proposed methods make it possible to simply obtain the necessary input information and obviously improve the demodulation characteristics in the receiver, which helps to increase the throughput and radius of coverage of the system.

The proposed interference suppression method and a block for such suppression are intended mainly for a receiver with a multi-user detection device, in which case they improve the demodulation quality and increase the system throughput.

The proposed interference suppression method and a block for such suppression can be used not only in parallel interference suppression structures, but also in sequential interference suppression structures without additional changes. Some variants of the present invention can also be used for other digital and analog communication systems having a mobile station with a control channel according to the IS-665 standard.

Industrial applicability

The present invention allows to overcome such disadvantages of the known technical solutions as the deterioration of the reliability of the received signal at its low power with possible decision errors or with the wrong decision, as well as the rapid deterioration of the characteristics in a multi-stage process due to cumulative errors. The present invention provides more accurate control and processing in the decision-making process for the signal and during its restoration, improves the accuracy of noise suppression and thereby improves the performance of the system. In addition, in the present invention, the system throughput is increased and the near-far effect on the characteristics of the system is reduced. Using a receiver with multi-user detection provided by the proposed BPP unit can improve the demodulation characteristics at the base station and increase the system throughput.

Claims (8)

1. A method of suppressing multi-user interference, comprising the following steps: a) the implementation of the composite expansion for the input signal of the main range by using the compression unit; b) implementing Walsh channel compression for the compressed signal to allocate user channels; c) multiplying the bit streams of each individual channel by the conjugate signal of the output estimate value from block A of the check estimate to eliminate the effect of multipath fading; d) sending the bit streams after they are multiplied into a decider for making a decision; e) determining the threshold for decision making when using the other two blocks B and C of the control assessment and on the basis of data on the number of users, types of channels and types of services provided by the system, and then making decisions on the input bit streams for which a decision should be made; and f) multiplying the bit streams for which the decision was made by the estimated output value from the control evaluation unit A to reconstruct the effect of multipath fading, and the subsequent reconstruction of the signal. 2. The method according to claim 1, in which step "d" in the decision-making process includes d1) receiving from the system such parameters as the number of users and types of channels or types of services; d2) defining information about channel types or service types; d3) a change in the coefficient K2 in the equation Threshold = K1 · K2 · E_B, taking into account the information obtained in step d2; d4) determining the number of users in the system at the moment; and d5) changing the coefficient K1 in the equation in step d3 taking into account the number of users. 3. The method according to claim 2, in which, at step d3, when the coefficient of K2 changes, the higher the transmission speed of the channel, the greater the value taken for K2, and the value of K2 corresponding to the convolutional code channel should be greater than the value corresponding to the channel with encoding turbo type. 4. The method according to claim 3, in which when changing the coefficients, K2 is first determined, and then K1, and the K2 value is increased substantially linearly with increasing channel transmission speed and changing the channel code type, while in practice, the K1 value is pre-set in the range of 2 -3, and then simulate the optimal value of K2 and check it for various transmission speeds of the channels and various types of codes. 5. The method according to claim 1, in which at step "e" the decision is made based on two thresholds, namely: if the bit power by which the decision is to be made is less than threshold 1 (T1), then the value "0" is taken, if the bit power by which a decision is to be made exceeds threshold 2 (T2), then the value "0" is also taken, in all other cases, the value is "1" or "-1". 6. The method according to claim 2, in which at step d3 the changes are performed according to the equation Threshold = K1 · K2 · K3 · E_B, while K3 is a confidence indicator with a value of at least 1. 7. The method according to claim 6, in which when changing the values, the output signal of the control evaluation unit C is first obtained, then calculate the measuring base "Bas" for E_B according to the equations

and Bas = b · E_C; evaluate whether E_B exceeds the value of 'Bas' and, if so, this indicates that the bit power is higher and the value of K3 needs to be reduced; then evaluate whether the value of K3 is reduced to a value less than 1 and, if so, then take K3 = 1; if E_B is less than 'Bas', then this indicates that the bit power is less and the value of K3 needs to be left unchanged or increased; and then they evaluate whether the K3 value has exceeded the MAX_K3 maximum, with MAX_K3 being an integer greater than 1. 8. A multi-user interference suppression unit including a compression unit, three control evaluation units A, B and C, a first multiplier device, an interface device, a resolver and a second multiplier device, the compression unit compressing the input signal and extracting a useful user signal from the full signal; on the one hand, the compressed signal is sent to three blocks of the control evaluation, on the other hand, the compressed bit stream is sent to the first multiplier; the interface device transposes the output signal of block A of the control assessment; the first multiplier device multiplies the compressed bit stream by a signal transposed through the interface device; the decider uses the output signals of blocks B and C of the control assessment and the system information to make a decision on the bit stream, according to which a decision should be made, leaving the first multiplier; the second multiplying device multiplies the signal produced by the deciding device by the signal at the output of block A of the control evaluation, and the multiplication result is an input signal of the next stage of the demodulator module.

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