A Coalitional and Two-Level Game Based Approach for Spectrum Leasing in MIMO Cooperative Cognitive Radio Networks

A Coalitional and Two-Level Game Based Approach for Spectrum Leasing in MIMO Cooperative... In this work, we studied the resource allocation problem in a spectrum leasing scenario in MIMO cooperative cognitive radio networks (MIMO-CCRN) with multi channels using a coalitional game based approach. It is proved that the best case is to group all primary users (PUs) and secondary users (SUs) in a set, where each PU is able to lease its unused spectrum to all SUs using a time-division based strategy and the SUs relay the primary signals, in return. As a result of such grouping, the grand coalition is formed. Then, the stability of the proposed coalitional game based approach is analyzed using the core concept. Afterwards, using the achievements of the first part, we investigate a practical scenario where the data rate of the primary system, falls below a minimum data rate requirement, and alternatively, the PU resorts to the leasing of its unused spectrum to SUs. However, it is guaranteed that the SUs perform as cooperatively as to meet the rate requirement of the primary system. Moreover, the benefits of cooperating with the primary system may not be exploited by the secondary system efficiently, if the SUs compete over the resources. We propose a two-level game based on the bargaining games to tackle the aforementioned problems. More specifically, we model the interactions between the primary and the secondary systems as the first level cooperative game and we utilize the bargaining games as the second level of the proposed framework to share the benefits of spectrum leasing among the cooperating SUs in a fair and efficient manner. The simulation results confirm the theoretical achievements. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

A Coalitional and Two-Level Game Based Approach for Spectrum Leasing in MIMO Cooperative Cognitive Radio Networks

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4198-z
Publisher site
See Article on Publisher Site

Abstract

In this work, we studied the resource allocation problem in a spectrum leasing scenario in MIMO cooperative cognitive radio networks (MIMO-CCRN) with multi channels using a coalitional game based approach. It is proved that the best case is to group all primary users (PUs) and secondary users (SUs) in a set, where each PU is able to lease its unused spectrum to all SUs using a time-division based strategy and the SUs relay the primary signals, in return. As a result of such grouping, the grand coalition is formed. Then, the stability of the proposed coalitional game based approach is analyzed using the core concept. Afterwards, using the achievements of the first part, we investigate a practical scenario where the data rate of the primary system, falls below a minimum data rate requirement, and alternatively, the PU resorts to the leasing of its unused spectrum to SUs. However, it is guaranteed that the SUs perform as cooperatively as to meet the rate requirement of the primary system. Moreover, the benefits of cooperating with the primary system may not be exploited by the secondary system efficiently, if the SUs compete over the resources. We propose a two-level game based on the bargaining games to tackle the aforementioned problems. More specifically, we model the interactions between the primary and the secondary systems as the first level cooperative game and we utilize the bargaining games as the second level of the proposed framework to share the benefits of spectrum leasing among the cooperating SUs in a fair and efficient manner. The simulation results confirm the theoretical achievements.

Journal

Wireless Personal CommunicationsSpringer Journals

Published: May 10, 2017

References

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