A Game-Theoretic Approach for Power Allocation in Bidirectional Cooperative Communication

Abstract

Cooperative communication exploits wireless broadcast advantage to confront the severe fading effect on wireless communications. Proper allocation of power can play an important role in the performance of cooperative communication. In this paper, we propose a distributed gametheoretical method for power allocation in bidirectional cooperative communication networks. In this work, we consider two nodes as data sources who want to cooperate in sending data to the destination. In addition to being data source, each source node has to relay the other's data. We answer the question: How much power each node contributes for relaying other node's data? We use Stackelberg game which is an extensive-form game to find a solution to this problem. The proposed method reaches equilibrium in only one stage. It is shown that there are more benefits when bidirectional cooperation is done between node pairs who are closer to each other. Simulation results show that the proposed method leads to fair solution and the nodes farther to the destination should contribute more power to cooperate with others.

Optimal Channel Selection Based on Online Decision and Offline Learning in Multichannel Wireless Sensor Networks

“…They are different from conventional channel selection strategies by taking advantage of the sense information around external environment to make a decision in the channel selection process. The intelligent methods can be broadly divided into two categories: the game-based category that focuses on applying game theoretical tools to make a real-time decision [5][6][7][12][13][14][15][16][17][18][19][20][21][22][23] and the learning-based category that focuses on introducing reinforcement learning techniques to select optimized resource [8][9][10][11][24][25][26][27][28][29][30][31].…”

“…Wang et al [15] and Cui et al [16] propose a pricing model based on Stackelberg game, in which the leader node formulates price list for follower node to access certain desirable channel. Recently, a new incentive scheme, called intervention, has gained utilization in [17][18][19]. These approaches aim at formulating several incentive mechanisms to achieve higher utility.…”

User cooperation analysis under eavesdropping attack: A game theory perspective

“…However, the leader and the follower are always fixed for the general Stackelberg game [8], [9], [15], [16]. In order to reflect the symmetrical structure of the cooperation period as shown in Fig.…”

“…Nash bargaining solution is adopted to provide user incentive to cooperate for the bits-per-energy efficiency in [7]. Resource allocation is solved through Stackelberg game by [8] and [9]. Some studies, such as [10], utilize the auction game to analyze cooperative communication.…”

Price-based power control in relay networks using Stackelberg game

“…Considering distributed methods, in [9], two auction-based methods are used for distributed relay selection and power allocation. In [10], the authors proposed a game-theoretic method for power allocation in bi-directional cooperative communication.…”