Differentiated Backoff Strategies for Prioritized Random Access Delay in Multiservice Cellular Networks

Abstract

In this paper, a novel prioritization mechanism for random access strategies in cellular networks is proposed. The proposed prioritized random access strategy sets different retransmission probabilities to users, depending on their priorities. First, a mathematical analysis method for simultaneously evaluating throughput and access delay, considering an infinite population model and different retransmission policies, is developed. Most of the previous related research has been done, considering both finite population and saturation conditions where all the nodes in the system always have a packet ready to be transmitted, and the transmission queue of each station is assumed to be always nonempty. This assumption is a good approximation for a local area network working at full capacity. However, in a cellular system, the assumptions of a finite population and every node in a cell always having a packet to transmit are not very realistic. Here, the analytical results consider a Poisson arrival process-which is more suitable for the traffic model in a cellular system-for the users in the cells. Then, considering slotted ALOHA as a random access strategy and the developed analysis method, the case where two different types of service exist (low-and high-priority users) is mathematically analyzed. With the proposed prioritized random access strategy, the average access delay achieved for the high priority users is always lower than that for the low-priority users. Additionally, a mathematical expression for the throughput is derived with and without service differentiation. Finally, two approaches for finding the optimum retransmission probabilities are developed; in the first approach, the number of backlogged packets is required, whereas a simpler and efficient alternative method requires only the knowledge of the mean new packet arrival rate. For the performance analysis, four of the most common backoff algorithms are considered: (1) Uniform (UB); (2) Binary Exponential (BEB); (3) Negative Exponential (XB); and (4) Geometric (GB).