Multichannel Opportunistic Spectrum Access Research Articles

Multi-channel opportunistic spectrum access: A mixed-scale decision perspective

Consider a slot-based opportunistic communication system consisting of one transmitter, one receiver, and N two-state Markov channels. In each K continuous time slots on a large time scale, the transmitter probes one of N channels and chooses one to access in each time slot of the K time slots on a small time scale. For each successful access, one unit of reward is obtained. To maximize the cumulated reward over a time horizon of T, the joint probing (on a large time scale) and accessing (on a small time scale) problem can be cast into a mixed-scale partially observable Markovian decision process which is proved to PSPACE-Hard. Then the mixed-scale sequential decision-making problem is simplified into a probing decision problem on a large time scale. Considering the huge computing complexity of the large-scale probing decision, we present a simple heuristic policy which is to probe the best or the second-best channel in terms of available probability under different probing conditions regarding missing detection rate and false alarm one. Next, we derive several sets of sufficient conditions for different scenarios under which the proposed heuristic policy is optimal. Finally, the results of numerical experiments verify our theoretical analysis.

Cost-Aware Learning and Optimization for Opportunistic Spectrum Access

In this paper, we investigate cost-aware joint learning and optimization for multi-channel opportunistic spectrum access in a cognitive radio system. We investigate a discrete time model where the time axis is partitioned into frames. Each frame consists of a sensing phase, followed by a transmission phase. During the sensing phase, the user is able to sense a subset of channels sequentially before it decides to use one of them in the following transmission phase. We assume the channel states alternate between busy and idle according to independent Bernoulli random processes from frame to frame. To capture the inherent uncertainty in channel sensing, we assume the reward of each transmission when the channel is idle is a random variable. We also associate random costs with sensing and transmission actions. Our objective is to understand how the costs and reward of the actions would affect the optimal behavior of the user in both offline and online settings, and design the corresponding opportunistic spectrum access strategies to maximize the expected cumulative net reward (i.e., reward-minus-cost). We start with an offline setting where the statistics of the channel status, costs and reward are known beforehand. We show that the the optimal policy exhibits a recursive double threshold structure, and the user needs to compare the channel statistics with those thresholds sequentially in order to decide its actions. With such insights, we then study the online setting, where the statistical information of the channels, costs and reward are unknown a priori. We judiciously balance exploration and exploitation, and show that the cumulative regret scales in O(log T). We also establish a matched lower bound, which implies that our online algorithm is order-optimal. Simulation results corroborate our theoretical analysis.

Performance of Joint Spectrum Sensing and MAC Algorithms for Multichannel Opportunistic Spectrum Access Ad Hoc Networks

We present an analytical framework to assess the link layer throughput of multichannel Opportunistic Spectrum Access (OSA) ad hoc networks. Specifically, we focus on analyzing various combinations of collaborative spectrum sensing and Medium Access Control (MAC) protocol abstractions. We decompose collaborative spectrum sensing into layers, parametrize each layer, classify existing solutions, and propose a new protocol called Truncated Time Division Multiple Access (TTDMA) that supports efficient distribution of sensing results in "k out of N" fusion rule. In case of multichannel MAC protocols we evaluate two main approaches of control channel design with (i) dedicated and (ii) hopping channel. We propose to augment these protocols with options of handling secondary user (SU) connections preempted by primary user (PU) by (i) connection buffering until PU departure and (ii) connection switching to a vacant PU channel. By comparing and optimizing different design combinations we show that (i) it is generally better to buffer preempted SU connections than to switch them to PU vacant channels and (ii) TTDMA is a promising design option for collaborative spectrum sensing process when k does not change over time.

Performance of Joint Spectrum Sensing and MAC Algorithms for Multichannel Opportunistic Spectrum Access Ad Hoc Networks

Performance of Joint Spectrum Sensing and MAC Algorithms for Multichannel Opportunistic Spectrum Access Ad Hoc Networks