On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance

Abstract

We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The problem is to design a sensing policy for channel selection to maximize the average reward, which can be formulated as a multi-arm restless bandit process. In this paper, we study the structure, optimality, and performance of the myopic sensing policy. We show that the myopic sensing policy has a simple robust structure that reduces channel selection to a round-robin procedure and obviates the need for knowing the channel transition probabilities. The optimality of this simple policy is established for the two-channel case and conjectured for the general case based on numerical results. The performance of the myopic sensing policy is analyzed, which, based on the optimality of myopic sensing, characterizes the maximum throughput of a multi-channel opportunistic communication system and its scaling behavior with respect to the number of channels. These results apply to cognitive radio networks, opportunistic transmission in fading environments, downlink scheduling in centralized networks, and resource-constrained jamming and anti-jamming.

Optimal Cognitive Access of Markovian Channels under Tight Collision Constraints

“…In [2], [6], Zhao et al consider the case when all users follow a slotted transmission structure: when a PU has packets to transmit, it will do so at the beginning of the slot. Imposing a slotted structure simplifies the problem considerably, thanks to the separation principle [7] and the optimality of myopic policies [8], [9].…”

Betting on Gilbert-Elliot channels

“…In that work, however, the channel state is assumed to be independent from slot to slot. In [8], [10], [12]- [14], the authors target the problem of optimal access to multiple Gilbert-Elliot channels. In their setup, a sensing action is always carried out by the secondary user before attempting any transmission.…”

Design and Analysis of Optimal Random Access Policies in Cognitive Radio Networks

“…A brief summary of relevant works is provided in Section II. At this time, there have been relatively few attempts at true cross-layer formulations that connect MAC layer performance to physical layer sensing [4], [5]. In this work, we focus on developing queuing models for dynamic cognitive MAC protocols -an area where the prior art is relatively sparse.…”

“…[10] jointly investigates channel sensing duration and search order optimization problems. In [5] a myopic sensing policy based on a partially observable Markov decision process (POMDP) framework is proposed. [4] suggests a new MAC protocol with two phases -reporting (wherein all SUs sense the channel state cooperatively) followed by negotiation-based channel access.…”

“…In [21] a queueing analytic framework is developed to study the MAC performance with opportunistic spectrum scheduling. The queueing performance of the myopic sensing policy [5] is analyzed by using a large deviation approach in [22]. In [23] the queueing delay of a cognitive radio network is analyzed where each SU that identifies an idle channel contends for it with a fixed probability.…”