Queuing Performance of Multichannel S-ALOHA Systems With Correlated Arrivals

Abstract

Abstract-In this paper, we examine the queuing performance of terminals in a multichannel centralized S-ALOHA system with a finite terminal population and finite queue size in each terminal, employing a uniform backoff (UB) algorithm with retry limit for collision resolution. The performance evaluations focus on uplink traffic from web browsing, which is modeled as a Markovmodulated Bernoulli process with correlated arrivals. We analyze the system performance in terms of system throughput, mean queue length, mean delay, the probability that a packet is dropped by retry limit, the probability that a packet is blocked by a full queue, and the mean and variance of packet retransmission time, in relation to the source correlation, number of channels, window size, and retry limit. For comparison, we also consider bufferless terminals with correlated arrivals. In addition, we evaluate by simulations the performance of terminals with finite queue size when they have perfect knowledge of the backlog size. Results from our study allow the parameters of the UB algorithm to properly be chosen to meet the access-level quality-of-service requirements.Index Terms-Access protocol, algorithm design and analysis, cellular networks, communication system signaling, multiaccess communication.

Analysis of Two-Step Random Access Procedure for Cellular Ultra-Reliable Low Latency Communications

“…At each RA slot period, a non-backlogged device can generate a packet with probability p, which is called packet generation probability. While different packet generation probability for each device may reflect a more practical network scenario, the analysis for the the same packet generation probability introduces the worst case scenario [30]. The two-step RA procedure is described as follows: This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

Analyzing the Synergy between Broadcast Polling and Piggybacking in WiMAX Networks

“…To prove the approximation formula in (22) let us start with the mean value analysis used to prove the Pollaczek-Khinchin formula [27]. In an M/G/1 system without vacations:…”

“…In a typical M/G/1 system E{S Q } = E{S} and the Pollaczek-Khinchin formula follows from (D.1). When server vacations of fixed size T fr are considered it can be proved that E{W } = E{W noV } + T fr /2 [27] and in combination with (D.1) we receive (22) where E{S 2 } can be approximated using (11) as Unlike a typical M/G/1 system, in our case the expected service delay for customers in the queue is not the same as the overall expected service delay, i.e., E{S Q } = E{S}. This is because only queued packets can enjoy the low delay of piggybacking.…”