Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications

Abstract

Cooperative-relaying networks have great potential for deployment in next-generation wireless communication networks. However, a cooperative-relaying network using two-dimensional multiple-input-multiple-output technology can further enhance the network performance. In this article, we propose a game theoretical framework for mobile twodimensional multiple-input-multiple-output communication networks to achieve optimal relay selection and cooperative control. A source node, relay, and destination node can make service-selection decisions dynamically in a two-level network, based on the mobile-channel satisfaction parameters (e.g. spatial-temporal correlation and relay survivability). To model this dynamic interactive decision problem, we propose a hierarchical dynamic game framework. At the outer level, we formulate an evolutionary game to model and analyze the process of adaptive selection of relays for maximizing the multiple-input-multiple-output capacity by relay selection and power allocation. At the inner level, by aligning relays, we formulate an evolutionary game to model a self-organizing network structure for relays, to increase the capacity. A closed-loop evolutionary game equilibrium is considered to solve the dynamic game. Numerical results show that the proposed algorithm can effectively improve the quality of service for mobile two-dimensional multiple-input-multipleoutput communication networks.

RETRACTED: Capacity maximization in multi-user multiple input multiple output cognitive radio system through optimal beamforming design using game theory

“…Monte Carlo simulation is carried out for 5000 channel coefficients and average system capacity is evaluated. Optimal power allocation is achieved through water filling algorithm as in equation (21). The proposed non-cooperative game theory algorithm forces the participating SUs to obtain the best responses in terms of SINR, based on which average CR capacity is evaluated.…”

“…There are advancements in various aspects of wireless communication such as cooperative communication, CR, 19,20 and game theory is widely used for parameter optimization in wireless sensor networks too. 21 In our work, the study mainly focuses on application of game theory on designing capacity efficient CR system using MIMO. Mathematical modeling of the system uses the concepts, theories, and methodologies of engineering design using game theory.…”

Evolutionary modeling and robustness analysis of multi-domain cooperative communication network under the environment of Internet of things

“…Failed to achieve the best performance of Cooperative communication fitness networks (CCFN) Feng 28 Complex networks It is superior to other search strategies in time and steps More complex network features such as weights are not considered Liu et al 30 Cooperative-relaying networks…”

“…A complex network search strategy combining maximum and minimum clustering coefficients is proposed, 28 which excellently controls the occupation of network resources by some unnecessary information. 29 A game theory framework for Mobile two-dimensional MIMO communication networks is proposed 30 to realize optimal relay selection and cooperative control. A new cooperative Non-orthogonal multiple access (NOMA) transmission scheme is proposed 31 for three-user downlink system, which is significantly superior to the prior art in terms of rate.…”