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In the third generation wireless communication, a system which has wideband, high speed, and ability to transmit multimedia traffic is primarily concerned. The CDMA (code division multiple access) systemis a good choice due to its high spectrum efficiency, soft capacity (or graceful degradation), multipath resistence, anti - jamming ability, inherent frequency diversity, and no cell planning requirement. Because for direct - sequence CDMA (DS - CDMA), the capacity is limited by interference level, the control of interference level is an important design issue.
In this paper, we first propose a pipeline recurrent neural network (PRNN) interference predictor for DS - CDMA / FRMA wireless systems. With the aid of predicted interference, the control of interference level can be more effectivly. Second, we propose a fuzzy / neural congestion controller which includes the PRNN interference predictor, fuzzy performance indicator, and fuzzy permission probability controller. According to the predicted interference and performance indicator, the congestion controller can adjust the permission probability to control the number of contention users and let the interference level be under a level. From simulation result, we can seethat the PRNN interference predictor has better performance than RLS interference predictor in prediction error and the improvement of prediction is about 7%. We can see also the PRNN interference predictor takes less time to convergence by comparing with RLS interference predictor, and the improvement is about 25 sec. And our congestion controller has better performance than DS - CDMA / PRMA with channel access function in corruption ratio, voice packet dropping ratio, and adaptive property to change of traffic source characteristic. To set the corruption ratio and voice packet, dropping ratio to the lvel of 0.01, our algorithm has the improvement about 36.67% and 15.15%, repectively.
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