Cooperative smartphone relay selection based on fair power utilization for network coverage extension

This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain's fairness index and utility of end devices in both symmetric and asymmetric network configurations

SUITABLE PARTNER SELECTION IN A DECENTRALISED COOPERATIVE COMMUNICATION VIA THE BUYER-SELLER GAME

The performance and efficiency of a cooperative diversity scheme depend, largely on proper allocation of resources like power and bandwidth. Another important factor to consider is the selection of a proper partner by the source node to help in forwarding information to the destination. In this letter, we look at the concept of relay selection for a distributed communication networks, rather than the more common centralized system where precise channel state information data has to be available at the base station. Also coded cooperation is used as the cooperative scheme rather than the more common amplify-and-forward or decode-and-forward system. A type of game known as non-cooperative game is employed in this analysis so as to jointly consider the utilities of the source and relay nodes, where in this case, the source is the buyer while the relay is the seller. The approach enables the source to maximize its benefit (or utility) by selecting to buy power from the relay that would enable it do so. Results show that at a low price, the source node buys more power from the relay, which also increases the utility of the relay itself. It also shows that among a set of relays competing for the attention of a source node, the source will only select a partner (relay) that gives it the highest utility in terms of the resource, i.e power. In this paper, partner and relay are used interchangeably

Dynamic Spectrum Allocation and Sharing in Cognitive Cooperative Networks

The dramatic increase of service quality and channel capacity in wireless networks is severely limited by the scarcity of energy and bandwidth, which are the two fundamental resources for communications. New communications and networking paradigms such as cooperative communication and cognitive radio networks emerged in recent years that can intelligently and efficiently utilize these scarce resources. With the development of these new techniques, how to design efficient spectrum allocation and sharing schemes becomes very important, due to the challenges brought by the new techniques. In this dissertation we have investigated several critical issues in spectrum allocation and sharing and address these challenges. Due to limited network resources in a multiuser radio environment, a particular user may try to exploit the resources for self-enrichment, which in turn may prompt other users to behave the same way. In addition, cognitive users are able to make intelligent decisions on spectrum usage and communication parameters based on the sensed spectrum dynamics and other users' decisions. Thus, it is important to analyze the intelligent behavior and complicated interactions of cognitive users via game-theoretic approaches. Moreover, the radio environment is highly dynamic, subject to shadowing/fading, user mobility in space/frequency domains, traffic variations, and etc. Such dynamics brings a lot of overhead when users try to optimize system performance through information exchange in real-time. Hence, statistical modeling of spectrum variations becomes essential in order to achieve near-optimal solutions on average. In this dissertation, we first study a stochastic modeling approach for dynamic spectrum access. Since the radio spectrum environment is highly dynamic, we model the traffic variations in dynamic spectrum access using continuous-time Markov chains that characterizes future traffic patterns, and optimize access probabilities to reduce performance degradation due to co-channel interference. Second, we propose an evolutionary game framework for cooperative spectrum sensing with selfish users, and develop the optimal collaboration strategy that has better performance than fully cooperating strategy. Further, we study user cooperation enforcement for cooperative networks with selfish users. We model the optimal relay selection and power control problem as a Stackelberg game, and consider the joint benefits of source nodes as buyers and relay nodes as sellers. The proposed scheme achieves the same performance compared to traditional centralized optimization while reducing the signaling overhead. Finally, we investigate possible attacks on cooperative spectrum sensing under the evolutionary sensing game framework, and analyze their damage both theoretically and by simulations

Blockchain-based distributive auction for relay-assisted secure communications

Physical layer security (PLS) is considered as a promising technique to prevent information eavesdropping in wireless systems. In this context, cooperative relaying has emerged as a robust solution for achieving PLS due to multipath diversity and relatively lower transmission power. However, relays or the relay operators in the practical environment are unwilling for service provisioning unless they are incentivized for their cost of services. Thus, it is required to jointly consider network economics and relay cooperation to improve system efficiency. In this paper, we consider the problem of joint network economics and PLS using cooperative relaying and jamming. Based on the double auction theory, we model the interaction between transmitters seeking for a particular level of secure transmission of information and relay operators for suitable relay and jammer assignment, in a multiple source-destination networks. In addition, theoretical analyses are presented to justify that the proposed auction mechanism satisfies the desirable economic properties of individual rationality, budget balance, and truthfulness. As the participants in the traditional centralized auction framework may take selfish actions or collude with each other, we propose a decentralized and trustless auction framework based on blockchain technology. In particular, we exploit the smart contract feature of blockchain to construct a completely autonomous framework, where all the participants are financially enforced by smart contract terms. The security properties of the proposed framework are also discussed

Energy Efficient Two-hop D2D Communications Underlay 5G Networks: A Stackelberg Game Approach

Although coverage and capacity are the key elements of the 5G user experience, a dominant part of the population living in rural areas still experience inferior connectivity. Several solutions have been proposed to address this issue. They include deploying small cells, increasing the number of sectors per eNodeB, and reusing signal repetition. However, most of them require complex deployment and expensive fees. Accordingly, many efforts have been deployed on coverage extension software. Even so, many critical issues related to public safety, relay capacity, and devices power constraints are still challenging. As a contribution, we propose in this paper a spectral and energy-efficient two-hop device to device (D2D) relay selection algorithm. Our main goal is to extend the connectivity to the out-of-coverage (OOC) devices. Contrarily to previous solutions in which the relay is selected centrally or individually, we propose a distributed two-stage algorithm based on the Stackelberg game to involve all the competing devices. In the first stage, the OOC devices (OCDUs) are matched with the relays maximizing their spectral efficiency, and the required bandwidth for each one is determined. Then, a power control stage is investigated to calculate the optimal transmission power. The numerical and simulation analysis shows that the proposed schema outperforms the former solutions in total system capacity, spectral efficiency (SE), and energy efficiency (EE) while reducing the complexity