On the bit estimators of partial parallel interference cancellation for DS-CDMA

In this paper, we propose an adaptive particle swarm optimization (APSO) based partial parallel interference cancellation scheme for direct-sequence code-decision multiple access (CDMA) communication system over frequency selective fading channels. However, the partial cancellation tries to reduce the cancellation error in parallel interference cancellation schemes due to the wrong interference estimations in the early stages. Thus, in order to reduce the computational complexity and improve the performacne of the CDMA system, particle swarm optimization (PSO), which has the ability of solution to complex combinatorial optimization problem, is employed in searching the optimal weight for multiple access interference cancellation. Experiments have been carried out on the method can improved on the multiuser detection in CDMA system, the simulation results show that APSO detector can achieve the global optimization in fast convergence rate, and also show that the proposed detector is obviously superior to convenentional receiver and multiuser detectors based on some optimum algorithm in terms of the multiple access interfere and the mitigation of near-far effect.

We comment on partial parallel interference cancellation as discussed in the paper by Divsalar et al. (see ibid. vol.46, p.258-68, 1998). The aforementioned work showed that by multiplying the symbol estimates by a factor less than unity in the early stages of cancellation, the performance of parallel cancellation can be improved relative to full ("brute force") cancellation. In this paper we analyze the improvement of parallel cancellation when using partial cancellation, and provide additional insight into the gains. Specifically, we show that the decision statistic is biased when linear (soft) estimates of the symbol or channel are used for cancellation. Partial cancellation improves the performance in this case by reducing the decision statistic bias.

This paper develops an improved generalized multistage multiuser detector that uses the partial interference cancellation approach developed by Divsalar. The detector that is proposed for uplink code-division multiple access systems uses the generalized multistage detector to produce the estimates of the received data. The regenerated multiuser interference is then weighted proportionally to the reliabilities and subtracted. The performance of the matched filter, the conventional multistage multiuser detector, the partial parallel interference cancellation detector and the proposed new detector are evaluated in Rayleigh fading channels. Finally, bit error rate results are presented versus signal-to-noise ratio. It shows that considerable improvement can be achieved by the proposed scheme in heavily loaded systems.

In this paper, we introduce a simple, closed-form expression for finding the optimum partial cancellation factors (PCF) for the linear multistage partial parallel interference cancellation (PPIC) receiver. These factors are found in a direct- sequence code division multiple access (DS-CDMA) system over a frequency-flat fading channel for a large-system case. In this case, the number of active users and the processing gain tend to infinity while their ratio is finite. It will be shown that the expression for the PCF is a function of the moments of the eigenvalues of the correlation matrix, the number of interference cancellation (IC) stages, the system load, and the signal-to-noise ratio (SNR). Compared to recently-proposed methods, our method has the following advantages: a) It is less complex because the calculated PCF will be a direct function of the moments of the eigenvalues of the large correlation matrix; b) there is no need for ordering the PCF resulting in lower complexity; and c) it is not necessary to know the number of IC stages ap riori .

Multiple access interference (MAI) is inevitable in all kinds of CDMA mobile communication systems. In order to decrease MAI efficiently parallel interference cancellation (PIC) was proposed, however, it would be injured by mistake decision. Thus a wide variety of partial parallel interference cancellation (PPIC) algorithms have been constructed so as to solve this problem. Under such background this paper applied basic fuzzy theory to PIC and generated a new PPIC algorithm — fuzzy parallel interference cancellation based on estimated signal-to-interference ratio (SIR-FPIC). Matlab simulation results showed that SIR-FPIC algorithm was able to lower the system bit error rate compared with conventional PIC and improve the reception capability.

We study partial parallel interference cancellation in a DS-CDMA system with timing errors. We show that by multiplying symbol estimates by a factor less than unity in early stages of cancellation, the performance of parallel cancellation can be improved relative to full ("brute force") cancellation. BER performance is a function of the factor and the "best factor" can be far less than one. In practical systems, timing errors need to be considered. This paper considers the effect of timing errors on the selection of "best factor". We show that due to the timing error the interference cancellation is less reliable and a smaller factor of cancellation need be employed.

The paper introduces an analytical tool to find the large-system performance of a multistage linear partial parallel interference cancellation (PPIC) receiver using the moments of the eigenvalues of the covariance matrix for a code division multiple access (CDMA) system over a frequency-flat fading channel. The figure of merit to evaluate the performance is the signal-to-interference-plus-noise ratio (SINR) that is calculated under a large-system condition. In this case, the number of active users and the processing gain tend towards infinity while their ratio is a fixed value. It is shown that the large-system performance is a function of the system load, the partial cancellation factor (PCF), the number of interference cancellation stages, the signal-to-noise ratio (SNR), and the received powers of the interfering users. Furthermore, for practical applications, the physical meaning of the large system is described by numerical simulations.

A multi-stage partial parallel interference cancellation receiver is proposed for the multi-rate DS-CDMA system which adopts the multiple processing gain scheme. In each stage of the proposed receiver, partial cancellation is performed with an adaptive decision threshold which is computed from the matched filter outputs of the previous stage. The BER performance of the proposed receiver is obtained by simulation in a Rayleigh fading channel. It is shown that the proposed receiver achieves smaller BER than the multi-stage parallel interference cancellation receiver and extended group-wise successive interference cancellation receiver in the multi-rate DS-CDMA system.

In this work, a novel particle swarm optimization (PSO) assisted Joint Channel Estimation and Partial Parallel Interference Cancellation (PSO-JCEPPIC) detector is adopted for multiuser Multiple-Input Multiple-Output/Space Division Multiple Access (MIMO-SDMA) Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed PSO-PPIC scheme tries to reduce the cancellation error in Conventional Parallel Interference Cancellation (CPIC) detection schemes used in MIMO SDMA-OFDM system. The PSO algorithm is employed in searching the optimal weights of the PPIC for multiple access interference cancellation. The proposed scheme is shown to provide a performance improvement as compared to MMSE and CPIC detectors especially in an overloaded scenario where the number of users is high as compared to the base station (BS) antennas. In this scenario, the channel coefficients become more difficult to be estimated, due to the high number of independent channel links and the constraint imposed by the MIMO channel matrix rank. The proposed PSO-JCEPPIC scheme presents an efficient solution to the multiuser detection and the MIMO channel matrix estimation dilemma in the previously mentioned scenario.

In this paper, a new scheme of Joint Channel Estimation and Partial Parallel Interference Cancellation using Simulating Annealing (SA) or Particle Swarm Optimization (PSO) algorithms is proposed. This scheme is proposed for multiuser Multiple-Input Multiple-Output /Space Division Multiple Access (MIMO-SDMA) Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed scheme tries to reduce the cancellation error in Conventional Parallel Interference Cancellation (CPIC) detection schemes used in MIMO SDMA-OFDM system. The SA and PSO algorithms are employed in searching the optimal weights of the PPIC for multiple access interference cancellation. The proposed scheme is shown to provide a performance improvement as compared to MMSE and CPIC detectors especially in an overloaded scenario where number of users is high as compared to the Base Station (BS) antennas. In this scenario, channel estimation becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated and the constraint imposed by the rank of the MIMO channel matrix. The proposed scheme provides a reasonable solution to the multiuser MIMO channel estimation problem and multiuser detection in the above-mentioned overloaded scenario.

Partial parallel interference cancellation in a DS-CDMA system with tracking errors is studied. The aforementioned work showed that by multiplying symbol estimates by a less than unity in the early stages of cancellation, the performance of parallel cancellation can be improved relative to full (brute force) cancellation. Shan and Rappaport (see IEEE GlobeCom'98, vol.3, p.2615-20, 1998) shows that the BER performance is a function of the and the best factor can be far less than one. In a practical system, tracking errors need to be considered. This paper considers the effect of timing errors on the selection of the best factor. We show that due to the timing error the interference cancellation is less reliable and a smaller of cancellation need to be employed.

This paper introduces a new multi-user detection method, successive interference cancellation based on the order of log-likelihood-ratio (LLR-SIC), for asynchronous code division multiple access (CDMA) systems. LLR-SIC operates on the fact that the most reliable user, i.e. the user with the largest log- likelihood-ratio (LLR) absolute value, should be first detected and cancelled from received signal. Simulation results show that LLR-SIC significantly outperforms partial parallel interference cancellation (P-PIC) over multi-path Rayleigh fading channels. And the results also show that LLR-SIC can even support overloaded systems in which the number of users is greater than the spreading factor.

Performance analysis of an adaptive two-stage PIC CDMA receiver in AWGN channels

Multi-User Shared Access is a non-orthogonal multiple access scheme of 5G,which has a high computational complexity and a large time delay due to the usage of successive interference cancellation detection algorithm. This paper proposes a multi-stage partial parallel interference cancellation detection algorithm, which does not require repeated ordering and repeated matrix inversion. In the first stage of detection, the bits of these users with good channel conditions will be outputted, and the influence of multiple access interference on users with bad channel conditions in the second stage will be decreased. Theoretical analysis and simulation results show that the symbol error rate of the proposed algorithm is slightly better than that of the two-stage MMSE-PIC, and the complexity is reduced. In the meanwhile, the computational complexity is significantly reduced without SER performance degradation when compared with MMSE-SIC algorithm.

Multiple-access interference (MAI) limits the performance of CDMA systems using the conventional receiver, but the optimal receiver is too complex for practical implementation. This paper demonstrates a numerically efficient technique for reducing MAI in CDMA systems. The technique, a nonlinear approach inspired by the Kalman filter, uses decoupled filters to estimate symbols for each user while accomplishing interference cancellation in the innovation term. The filter technique developed here provides a computationally practical approach to multiuser detection for asynchronous long code systems, which significantly outperforms the conventional receiver. Kalman filter approaches to multiuser detection have been applied before (Lim and Ma 2000, Lim et. al. 1998) to binary phase shift keying through implementation of a standard Kalman filter approach. Unfortunately, this leads to high computational complexity. Here, we instead consider a formulation in which the spreading codes are viewed as random and their properties are used to decouple the Kalman filter for each user. Interference cancellation is then implemented through the innovations. A binary minimum mean squared error estimate is made, which results in a nonlinear estimator. The new nonlinear technique is shown to significantly outperform an optimized partial parallel interference cancellation approach, which is the current state of the art technique for asynchronous long code systems. System capacity is then significantly increased.