Multiuser Detection for Out-of-Cell Cochannel Interference Mitigation in the IS–95 Downlink

This paper considers the application of multiuser detection techniques to improve the quality of downlink reception in a multi-cell IS–95 digital cellular communication system. In order to understand the relative performance of suboptimum multiuser detectors including the matched filter detector, optimum multiuser detection in the context of the IS–95 downlink is first considered. A reduced complexity optimum detector that takes advantage of the structural properties of the IS–95 downlink and exhibits exponentially lower complexity than the brute-force optimum detector is developed. The Group Parallel Interference Cancellation (GPIC) detector, a suboptimum, low-complexity multiuser detector that also exploits the structure of the IS–95 downlink is then developed. Simulation evidence is presented that suggests that the performance of the GPIC detector may be near-optimum in several cases. The GPIC detector is also tested on a snapshot of on-air data measured with an omnidirectional antenna in an active IS–95 system and is shown to be effective for extracting weak downlink transmissions from strong out-of-cell cochannel interference. The results of this paper suggest that the GPIC detector offers the most performance gain in scenarios where weak downlink signals are corrupted by strong out-of-cell cochannel interference.     

Reduced-state maximum-likelihood multiuser detection for down-linkTD-CDMA systems

In order to defeat both intersymbol and multiple access interference arising in code division multiple access systems, numerous multiuser detection techniques have been investigated . Actually, the computational complexity of the optimum maximum-likelihood multiuser detector (MLMD) increases exponentially with the number of users, therefore it is infeasible. We propose two suboptimum versions of MLMD, especially designed for down-link connections, which are based on a computational efficient reduced-state technique. It has been found that these algorithms have a significant performance gain as compared with other suboptimum joint detection criteria, such as zero forcing and minimum mean squared error. Moreover, they have a computational complexity which is proportional to the number of users     

A new approach to greedy multiuser detection

We propose a new suboptimum multiuser detector for synchronous and asynchronous multiuser communications. In this approach, a greedy strategy is used to maximize the cost function, the maximum-likelihood (ML) metric. The coefficients of the ML metric are utilized as weights indicating in which order bits can be estimated. The complexity of the algorithm is approximately K/sup 2/ log K per bit, where K is the number of users. We analyze the performance of the greedy multiuser detection in the additive white Gaussian noise channel as well as in the frequency-nonselective Rayleigh fading channel, and compare it with the optimum detector and several suboptimum schemes such as conventional, successive interference cancellation, decorrelator, sequential, and multistage detectors. The proposed greedy approach considerably outperforms these suboptimum schemes, especially for moderate and high loads in low and moderate signal-to-noise ratio regions. The results show that when there is a significant imbalance in the values of the coefficients of the ML metric due to moderate to high noise, fading, and asynchronous transmission, near-optimum performance is achieved by the greedy detection.     

A gradient guided search algorithm for multiuser detection

This paper introduces a new multiuser detection algorithm based on a gradient guided search that can achieve near-optimum performance while its implementation complexity is linear in the number of users. The new algorithm attempts to perform jointly optimum multiuser detection by updating one user's bit decision each iteration in the best possible way. When a decorrelating multiuser detector is employed to initialize the proposed algorithm, in all cases tested the gradient guided search converges to a solution with performance very close to optimum. Further, tests indicate that the proposed algorithm provides excellent performance for cases where other suboptimum algorithms perform poorly. Although we focus only on synchronous multiuser detection, the algorithm is equally applicable to asynchronous multiuser detection problems     

SINR Enhancement Techniques for an IS-95 Downlink SIC Receiver

Due to near-far effects and multiple-access interference, several types of multiuser detectors have been developed in recent years to reliably demodulate user signals in a code-division multiple-access (CDMA) system. The downlink of Interim Standard 95 (IS-95) is particularly well suited to one such detector known as the successive interference canceler (SIC). In order to keep the receiver complexity low, entire base station signals are typically canceled in the receiver in a sequential manner. However, for the SIC to operate effectively, a base station signal that is being canceled must be reconstructed with enough accuracy such that sufficient interference power is removed for the subsequent base station to be reliably detected. If this is not possible, it may be necessary to employ techniques, specific to the signal format specified in the IS-95 downlink, which enhance the received signal-to-interference-plus-noise ratio (SINR). In this paper, we explore the performance gains achieved with several SINR enhancement techniques, and present computer simulations to demonstrate this improvement for example cochannel signal scenarios.     

一种改进的子空间盲多用户检测法

本文在常规子空间盲多用户检测方法的基础上进行改进,提出一种改进的子空间盲多用户检测方法.既考虑小区内用户的干扰,也考虑来自小区外用户的干扰,将接收信号空间可以分解成三个子空间,通过对子空间模型的修改和子空间跟踪算法的改进,解决快速矩阵分解的问题,降低接收机的复杂度,在收敛速度、稳定性方面也有所提高.     

基于粒子滤波算法的DS-CDMA多用户检测

粒子滤波算法是一种基于贝叶斯估计的蒙特卡罗方法,尤其适用于处理非线性、非高斯系统的状态估计问题。该算法应用于DS-CDMA系统的多用户检测中,检测器能在检测性能和计算复杂度之间取得很好的平衡。基于粒子滤波算法的多用户检测器在性能上逼近于最优多用户检测器,而计算复杂度远低于最优多用户检测器,与次优多用户检测器相当。利用白化匹配滤波器的输出可以建立同步DS-CDMA系统的状态空间方程,使得粒子滤波算法应用于多用户检测中。仿真实例证明了基于粒子滤波算法的多用户检测器在等功率和远近效应的情况下的性能优势。     

Suboptimum soft-output detection algorithms for coded multiuser systems

In this paper, we consider coded asynchronous multiuser signals in an additive white Gaussian noise channel. Since optimum joint multiuser detection (MUD) and forward error correction (FEC) decoding is characterized with a very high computational complexity, we consider disjoint MUD and FEC decoding. The optimum disjoint multiuser detector is the soft-output maximum a posteriori detector that provides sequences of a posteriori probabilities to the corresponding FEC decoders. It involves backward and forward recursions resulting in high complexity and processing delay. In this paper, we consider several suboptimum soft output disjoint multiuser detectors that involve only forward recursions and have reduced complexity and delay.     

Near-Optimum Iterative Multiuser Receiver for FEC Encoded DS-CDMA

The powerful iterative algorithm of Turbo code is employed in the proposed iterative multiuser receiver for the downlink of a forward error correction (FEC) coded direct-sequence code-division multiple access (DS-CDMA) environment. The receiver iterates between the 2 coding dimensions, namely the spreading codes and the FEC codes. The optimum iterative multiuser receiver uses the optimum decentralised single-user detector to generate the single-user extrinsic information for the single-user decoders. This paper suggests a near-optimum detector using a folded trellis preselection stage for the multiuser signal detection, in order to reduce the dominating complexity of the optimum decentralised detector. Simulation results show that performance is close to optimum. The effect of the single-user decoders' extrinsic information on the signal detection stage is also investigated and it is found that extrinsic information improves performance.     

CDMA multiuser detection: a nonlinear programming approach

The optimum receiver to detect the bits of multiple code-division multiple access (CDMA) users has an exponential complexity in the number of active users in the system. Consequently, many suboptimum receivers have been developed to achieve good performance with less complexity. We take the approach of approximating the solution of the optimum multiuser detection problem (OMUD) using nonlinear programming relaxations. First, we observe that some popular suboptimum receivers indeed correspond to relaxations of the optimal detection problem. In particular, one proposed approximation method yields to iterative solutions which correspond to previously proposed heuristic nonlinear detectors. Using a nonlinear programming approach, we identify the convergence properties of these iterative detectors. Secondly, we propose a relaxation that yields a receiver which we call the generalized minimum mean squared error detector. We give a simple iterative implementation of the detector. Its performance is evaluated and comparisons to other suboptimum detection schemes are given