Performance of DS-CDMA systems with optimal hard-decision parallel interference cancellation

R. Hofstad, M. J. Klok
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引用次数: 15

Abstract

We study a multiuser detection system for code-division multiple access (CDMA). We show that applying multistage hard-decision parallel interference cancellation (HD-PIC) significantly improves performance compared to the matched filter system. In (multistage) HD-PIC, estimates of the interfering signals are used iteratively to improve knowledge of the desired signal. We use large deviation theory to show that the bit-error probability (BEP) is exponentially small when the number of users is fixed and the processing gain increases. We investigate the exponential rate of the BEP after several stages of HD-PIC. We propose to use the exponential rate of the BEP as a measure of performance, rather than the signal-to-noise ratio (SNR), which is often not reliable in multiuser detection models when the system is lightly loaded. We show that the exponential rate of the BEP remains fixed after a finite number of stages, resulting in an optimal hard-decision system. When the number of users becomes large, the exponential rate of the BEP converges to (log 2)/2 $1/4. We provide guidelines for the number of stages necessary to obtain this asymptotic exponential rate. We also give Chernoff bounds on the BEPs. These estimates show that the BEPs are quite small as long as k = o(n/log n) when the number of stages of HD-PIC is fixed, and even exponentially small when k = O(n) for the optimal HD-PIC system, and where k is the number of users in the system and n is the processing gain. Finally, we extend the results to the case where the number of stages depends on k in a certain manner. The above results are proved for a noiseless channel, and we argue that we expect similar results in a noisy channel as long as the two-sided spectrum of the noise decreases proportionally to n.
最优硬决策并行干扰消除DS-CDMA系统的性能
研究了一种码分多址(CDMA)多用户检测系统。我们的研究表明,与匹配滤波器系统相比,采用多级硬判决并行干扰消除(HD-PIC)显着提高了性能。在(多级)HD-PIC中,迭代地使用干扰信号的估计来提高对所需信号的了解。我们利用大偏差理论证明,当用户数量固定且处理增益增加时,误码概率(BEP)呈指数小。我们研究了在HD-PIC的几个阶段后,BEP的指数速率。我们建议使用BEP的指数率作为性能度量,而不是信噪比(SNR),当系统负载较轻时,信噪比在多用户检测模型中通常不可靠。我们证明了在有限个阶段后,BEP的指数率保持固定,从而产生最优硬决策系统。当用户数量变大时,BEP的指数率收敛于(log 2)/2 $1/4。我们提供了获得此渐近指数率所需的阶段数的指南。我们还给出了bep的切尔诺夫界。这些估计表明,当HD-PIC级数固定时,只要k = o(n/log n), bep就相当小,对于最优HD-PIC系统,当k = o(n)时,bep甚至呈指数级小,其中k为系统中的用户数量,n为处理增益。最后,我们将结果推广到阶段数以某种方式依赖于k的情况。上述结果在无噪声信道中得到了证明,我们认为,只要噪声的双边频谱与n成比例地减小,我们期望在有噪声信道中得到类似的结果。
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