Title

Queue-Aware Opportunistic Scheduling In Multi-Channel Dynamic Spectrum Access Networks

Keywords

cognitive radio; Dynamic spectrum access; fairness; scheduling; SINR; throughput

Abstract

In this paper, we propose an opportunistic scheduling algorithm for secondary users (SUs) in a dynamic spectrum access network. Scheduling is performed at the beginning of each super-frame where appropriate channel(s) are assigned to the SUs based on the expected throughput that each channel provides. We compute the expected throughput for each channel on specific time slots in a super-frame based on three factors: i) primary channel occupancy, ii) signal-to-interference-and-noise ratio, and iii) back-logged queue length of the SUs. We consider scheduling both on a frame-by-frame basis and also on a slot-by-slot basis. The state transitions are modeled using a discrete-time Markov chain (DTMC) process and their probabilities are calculated. The state transitions occur at the frame/slot boundaries. Multiple SUs are allocated the same channel on the same time slot as long as there is no interference between them. Such non-interfering sets of SUs is found by considering the expected throughput of each user on all candidate channels. In order to maximize spatial and temporal reuse of channels, the non-interfering sets are assigned to as many channels as possible on maximum possible time slots. Performance of the proposed scheduling schemes is validated using simulations where we measure metrics such as throughput, number of slots allocated, fairness, and blocking probability. We also show the efficacy of the queue-aware scheduling by comparing with one that does not consider the queues.

Publication Date

7-10-2017

Publication Title

18th IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks, WoWMoM 2017 - Conference

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/WoWMoM.2017.7974292

Socpus ID

85027493374 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85027493374

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