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We formulate and study a multi-user multi-armed bandit problem that exploits the temporal–spatial opportunistic spectrum access (OSA) of primary user (PU) channels, so that secondary users (SUs) who do not interfere with each other can make use of the same PU channel. We first propose a centralized channel allocation policy that has logarithmic regret, but requires a central processor to solve an NP-complete optimization problem at exponentially increasing time intervals. To overcome the high computation complexity at the central processor, we also propose heuristic distributed policies that, however, have linear regrets. Our first distributed policy utilizes a distributed graph coloring and consensus algorithm to determine SUs’ channel access ranks, while our second distributed policy incorporates channel access rank learning in a local procedure at each SU at the cost of a higher regret. We compare the performance of our proposed policies with other distributed policies recently proposed for temporal (but not spatial) OSA. We show that all these policies have linear regrets in our temporal–spatial OSA framework. Simulations suggest that our proposed policies have significantly smaller regrets than the other policies when spectrum temporal–spatial reuse is allowed. [ABSTRACT FROM AUTHOR]

In recent wireless network domains static spectrum access is a major concern. Generally, this access leads to spectrum scarcity problem by creating empty holes or white spaces. However, the scarcity is temporary and can be alleviated if spectrum access is performed dynamically and efficiently. One important step towards dynamic spectrum access is the development of cognitive radio (CR) technology, which senses nearby spectrum portions (or bands) and tries to use them either opportunistically or by negotiating with the neighboring users. Nonetheless, dynamic spectrum access raises several challenges which need to be addressed in detail. These challenges include efficient allocation of spectrum for users in order to maximize spectrum utilization and to avoid user level conflicts both under licensed and unlicensed bands. In this paper, considering the relative rarity of solutions for unlicensed spectrum access and their inadequacy, we propose a scheme, where the CR devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing and they allow other CR users to enter in their vicinity of acquired spectrum via bilateral message exchanges. Further, we present continuous time Markov chains to model the spectrum access process in continuous time and derive important performance metric as the blocking probability for without and with queuing systems. Amongst others, the important comparisons we made between analytical and simulation results in terms of blocking probability verify that our proposed model is correct. In essence, our proposed solution aims to increase dynamic spectrum usage by enabling cooperation between the users. [ABSTRACT FROM AUTHOR]

Energy efficiency (EE) is of great concern in cognitive radio networks since the throughput and energy consumption of secondary users (SUs) vary with the sensing time. However, the conditions of the detection probability and false alarm probability should be respected to better protect primary users (PUs) and to improve the sensing performance of SUs. Additionally, the PUs' minimum averaged power provision should also be regarded as a key problem of interactive linking to SUs. Therefore, an integrated design between the PU and SUs is desired for the coordination of the whole cognitive radio system, especially regarding the satisfaction of EE and performance metrics. This study formulates sensing constraints in a unified way and calculates the minimum SNR of SUs, based on which the essential PU power provision is computed. Furthermore, EE is proved as a decreasing function with the PU's active ratio, where the maximum EE is obtained corresponding to the minimum QoS requirements of the sensing process. Hence, a bisection-based method is proposed to maximize EE, which is considered as a concave function of SUs' sensing time and has only one unique optimum. EE's optimization was analyzed under different fusion rules for diverse SNR conditions. The optimum was also studied with sensing performance targets for various cases of PU power provision. [ABSTRACT FROM AUTHOR]