Bursty Data Over CDMA: MAI Self Similarity, Rate Control and Admission Control

We study bursty data communications in the downlink in random-access code division multiple access (CDMA) systems. We first present a new model that simultaneously takes into account the traffic information and fading channel characteristics for studying the multiaccess interference (MAI), and characterize the MAI from a stochastic process perspective. This new approach enables us to understand the temporal correlation structure. Our finding reveals that the MAI exhibits scale-invariant burstiness and is “self similar” across multiple time scales. The MAI self similarity indicates the existence of a nontrivial predictive MAI structure, which we exploit to conduct resource allocation for interference management. In particular, we utilize the MAI structure for interference prediction, built on which we carry out rate control and admission control. Our rate control scheme, based on multiple time-scale MAI prediction, uses a combination of variable spreading gain and adaptive coding. Our results show that this rate control scheme achieves better performance than that of the packet-level predictor, and can yield significant performance gain. We also devise a joint rate control and admission control scheme. Specifically, observation time windows are divided into slots, and rate control based on interference prediction is conducted in each slot. Then, the corresponding throughput in each observation window is used for admission control. We show that the above algorithm achieves high prediction accuracy and might well be useful for admission control for data applications. We also investigate the impact of feedback delay and data burstiness on the system performance. Keywords— CDMA, rate control, admission control, self similarity, fading channels.