A suboptimal joint bandwidth and power allocation for cooperative relay networks: a cooperative game theoretic approach

Abstract

In commercial networks, user nodes operating on batteries are assumed to be selfish to consume their resources (i.e., bandwidth and power) solely maximizing their own benefits (e.g., the received signal-tonoise ratios (SNRs) and datarates). In this paper, a cooperative game theoretical framework is proposed to jointly perform the bandwidth and power allocation for selfish cooperative relay networks. To ensure a fair and efficient resource sharing between two selfish user nodes, we assume that either node can act as a source as well as a potential relay for each other and either node is willing to seek cooperative relaying only if the datarate achieved through cooperation is not lower than that achieved through noncooperation (i.e., direct transmission) by consuming the same amount of bandwidth and power resource. Define the cooperative strategy of a node as the number of bandwidth and power that it is willing to contribute for relaying purpose. The two node joint bandwidth and power allocation (JBPA) problem can then be formulated as a cooperative game. Since the Nash bargaining solution (NBS) to the JBPA game (JBPAG) is computationally difficult to obtain, we divide it into two subgames, i.e., the bandwidth allocation game (BAG) and the power allocation game (PAG). We prove that both the subgames have unique NBS. And then the suboptimal NBS to the JBPAG can be achieved by solving the BAG and PAG sequentially. Simulation results show that the proposed cooperative game scheme is efficient in that the performance loss of the NBS result to that of the maximal overall data-rate scheme is small while the maximal-rate scheme is unfair. The simulation results also show that the NBS result is fair in that both nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance.

A study of power allocation in multi-MRN aided multiuser networks

“…In this paper the decoded-and-forward (DF) scheme is used in downlink at each MRN since it enables users to exploit full spatial diversity [6,13]. Because the parameter of VPL is assumed as high as 25 dB in this paper, for the MRN assisted transmission mode the combing of signal received in sub-slot 1 and sub-slot 2 is not considered at user terminal.…”

“…The first term in (6) represents the capacity of the backhaul link and the second term in (6) represents the capacity of the access link. The factor of 1/2 is due to the time division multiplexing that two time sub-slots are occupied under the MRN assisted transmission mode [13].…”

“…The potential capacity and coverage improvement with deploying coordinated and cooperative relay nodes on top of trains have been shown in [3][4][5]. A cross-layer design jointly incorporating relay nodes selection and power allocation to increase the network lifetime is proposed in [6]. Through minimizing the asymptotic outage probability, an optimal power allocation scheme is developed in a multiuser relay network [7].…”

Orthogonal resource sharing scheme for device-to-device communication overlaying cellular networks: a cooperative relay based approach

“…Without loss of generality, we employ the half-duplex amplify-and-forward (AF) cooperation protocol [10,11] in the system. The CR for the cellular uplink transmission aided by the ith D2D transmitter UE T i consists of the following two stages.…”

“…In the second stage, UE T i helps the cellular uplink transmission by amplifying and retransmitting part of the information received from UE C in the first stage. Then the BS could combine the information received from UE C in the first stage and the information received from UE T i in the second stage using maximal ratio combining (MRC) method [11]. Under the assumption of a block fading channel model where the channel gains are fixed during any two stages for a CR and can change across any duration that is more than the two stages, we can express the achievable rate for the cellular communication after applying the CR-based bandwidth re-allocation as…”