Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory

Abstract

In this paper, a novel algorithm is proposed for increasing the throughput in cognitive radio networks by forming coalitions among cognitive radio users in AWGN and fading channel environment. Although there have been numerous studies exploring the benefits of coalition formation in cognitive radio networks from the game theory perspective, there are several limitations in their application. To overcome the limitations of game theory, concepts from matching theory are used. Specifically, the stable marriage problem is used to formulate the interactions among the cognitive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. The utility function is defined as the average probability of false alarm per cognitive radio user. The advantage of stable marriage is that it always converges to a stable matching and is Pareto optimal when the preferences of cognitive radios are strict. In the proposed model, the stable matching problem is extended to propose a novel algorithm to form coalitions of varying sizes for improving the utility of CR (false alarm and throughput). The coalitions formed using the algorithm are stable and do not deviate from the final matching. Using simulations and mathematical analysis, it is shown that the proposed algorithm leads to stable coalitions and returns significant improvement in terms of reduced probability of false alarm and improved throughput per cognitive radio user as compared to the noncooperative scenario.

Distributed coalition formation game for enhancing cooperative spectrum sensing in cognitive radioad hocnetworks

“…The proposed game is based on a merge‐only method that incorporates a handover or power control interference schemes. A stable marriage algorithm [35] is proposed for increasing the throughput in CRNs by forming coalitions among SUs in additive white Gaussian noise (AWGN) and fading channel environment. This algorithm formulates stable coalitions and provides significant improvement in terms of reduced and improved throughput per SU.…”

Fusion Rule Based on Dynamic Grouping for Cooperative Spectrum Sensing in Cognitive Radio

“…Average power P m can incorporate the effects of fading and shadowing, and P m = σ 2 sm . Consistent with [21], we define P m = µP/d α m , where P is the PU transmitted signal power, d m is the distance between PU and SU m . Moreover, µ is a unitless constant that depends on the antenna characteristics, and α is a path-loss exponent, respectively.…”