Proposal of an advanced MMSE multiuser receiver for a DS-CDMA environment using neural networks

In the last decade, Code Division Multiple Access (CDMA) has gained even more importance due to its capabilities of wider band occupancy without any time constraints. A lot of the recent implemented systems for wireless communications, as Universal Mobile Telecommunication System (UMTS) or IEEE 802.11b Wireless Local Area Network (WLAN), use the CDMA approach to allow the simultaneous access of multiple users. One of the main drawbacks of CDMA systems is the so called Multiple Access Interference (MAI). In the literature, several multiuser receivers were developed. Among them, receivers that perform mean square error minimization are very attractive for their very simple implementation. On the other hand, neural networks have gained recently an increasing importance due to their capabilities in solving many engineering problems, involving minimization of errors or some other cost functionals. In this paper, an advanced MMSE receiver based on the use of neural networks is proposed, where at every bit time neural network achieves the optimum values for the coefficient set of receiving filter, thus minimizing the error rate.