Search

Recent advances in loop interference cancelation techniques enable full-duplex relaying (FDR) systems, which transmit and receive simultaneously in the same band with high spectrum efficiency. Meanwhile, wireless virtualization has attracted a lot of attention from both academia and industry because it can provide more flexibility, diversity, and other benefits in the process of wireless network design, construction, operation, and management. In this paper, we introduce the idea of wireless virtualization into FDR cellular networks. Then, the problem of energy-aware virtual resource management is formulated as a three-stage Stackelberg game. The subgame perfect equilibrium for each stage is analyzed. In addition, the interplays of the three-stage game are discussed, and an iterative algorithm is proposed to obtain the Stackelberg equilibrium solution. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

Heterogeneous wireless networks are considered as promising technologies to improve energy efficiency. In heterogeneous networks, interference management is very important since the interference due to spectrum sharing can significantly degrade overall performance. In the existing work, various resource allocation methods are proposed to either improve energy efficiency or mitigate interference in orthogonal frequency-division multiple access (OFDMA)-based multicell networks. To the best of our knowledge, no research on resource allocation has jointly considered improving energy efficiency and performing interference control, especially using interference power constraint strategies. Furthermore, most existing work assumes that all of the channel state information (CSI) is known completely, which might not be realistic in heterogeneous networks due to the limited capacity of the backhaul links and varied ownership of network devices. In this paper, we propose a game-theoretical scheme using energy-efficient resource allocation and interference pricing for an interference-limited environment in heterogeneous networks. We formulate the problems of resource allocation and interference management as a Stackelberg game with incomplete CSI. A backward induction method is used to analyze the proposed game. A closed-form expression of the Stackelberg equilibrium (SE) is obtained for the proposed game with various interference power constraints. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of distributed mode selection, resource allocation, and interference management is studied for device-to-device (D2D) communications underlaying future cellular networks. In existing underlaid D2D communications, the base station (BS) typically assists D2D pairs in selecting a transmission mode to operate in (network-assisted), that is, either cellular, dedicated, or reuse mode. Network-assisted D2D communications assumes the BS has global knowledge of the network, which includes complete channel state information (CSI). However, acquiring global network information causes signaling overhead and network complexity to increase, due to the large number of users in the network. Therefore, we investigate user-assisted D2D communications as a viable solution for D2D communications, in which the BS has partial knowledge of the network (and partial CSI). To address this problem, a cross-layer coalitional (CLC) game is formulated, where D2D pairs and cellular users are clustered into coalitions based on resource allocation/sharing and mode selection, in a fully distributed and autonomous manner. Clustering D2D pairs allows resources to be shared fairly amongst users in a cluster, while also ensuring D2D pairs operate efficiently. To coordinate the interference between cellular and D2D pairs, an interference management subproblem is proposed that schedules D2D pairs reusing cellular user resources, as well as minimizing the transmission power of all users. To solve this game, a distributed algorithm is proposed, which converges to a Nash stable coalition partition that is socially efficient and has a nonempty core. Simulation results show that the proposed approach can effectively cluster D2D pairs into coalitions based on resource allocation and mode selection, which, in turn, reduces network sum power and increases network sum rate across all D2D pairs. [ABSTRACT FROM AUTHOR]

The high-speed railway wireless communication network architecture is gradually transforming from a traditional GSM-Railway (GSM-R) cellular network to a 5G heterogeneous ultra-dense communication network. How to effectively deal with the interference while obtaining the capacity gain has become an inevitable problem. This article proposes a power allocation interference alignment algorithm based on game equilibrium with the goal of joint optimization about throughput and energy efficiency for imperfect channels in high-speed railway communication. Firstly, the imperfect Channel State Information including delay and fading is calculated. Then, in order to improve system throughput and energy efficiency, we establish a game model and prove the existence of Nash equilibrium in the model. At the same time, a power allocation iterative algorithm based on Recurrent Neural Network is proposed. Finally, combined with the interference alignment algorithm based on a maximal signal-to-noise ratio, the optimal power matrix is calculated by iteration to achieve interference management optimization. The simulation results prove that our algorithm has superior performance in improving the system throughput, energy efficiency and transmission reliability in high-speed railway wireless communication with imperfect channels. [ABSTRACT FROM AUTHOR]