Device-to-device communications: a performance analysis in the context of social comparison-based relaying

Device-to-device (D2D) communications are recognized as a key enabler of future cellular networks which will help to drive improvements in spectral efficiency and assist with the offload of network traffic. Among the transmission modes of D2D communications are single-hop and relay assisted multi-hop transmission. Relay-assisted D2D communications will be essential when there is an extended distance between the source and destination or when the transmit power of D2D user equipments (UEs) is constrained below a certain level. Although a number of works on relay-assisted D2D communications have been presented in the literature, most of those assume that relay nodes cooperate unequivocally. In reality, this cannot be assumed since there is little incentive to cooperate without a guarantee of future reciprocal behavior. Cooperation is a social behavior that depends on various factors, such as peer comparison, incentives, the cost to the donor and the benefit to the recipient. To incorporate the social behavior of D2D relay nodes, we consider the decision to relay using the donation game based on social comparison and characterize the probability of cooperation in an evolutionary context. We then apply this within a stochastic geometric framework to evaluate the outage probability and transmission capacity of relay assisted D2D communications. Through numerical evaluations, we investigate the performance gap between the ideal case of 100% cooperation and practical scenarios with a lower cooperation probability. It shows that practical scenarios achieve lower transmission capacity and higher outage probability than idealistic network views which assume full cooperation. After a sufficient number of generations, however, the cooperation probability follows the natural rules of evolution and the transmission performance of practical scenarios approach that of the full cooperation case, indicating that all D2D relay nodes adopt the same dominant cooperative strategy based on social comparison, without the need for enforcement by an external authority

CSMA Local Area Networking under Dynamic Altruism

In this paper, we consider medium access control of local area networks (LANs) under limited-information conditions as befits a distributed system. Rather than assuming "by rule" conformance to a protocol designed to regulate packet-flow rates (e.g., CSMA windowing), we begin with a non-cooperative game framework and build a dynamic altruism term into the net utility. The effects of altruism are analyzed at Nash equilibrium for both the ALOHA and CSMA frameworks in the quasistationary (fictitious play) regime. We consider either power or throughput based costs of networking, and the cases of identical or heterogeneous (independent) users/players. In a numerical study we consider diverse players, and we see that the effects of altruism for similar players can be beneficial in the presence of significant congestion, but excessive altruism may lead to underuse of the channel when demand is low

Distributed Cooperative Transmission with Unreliable and Untrustworthy Relay Channels

Cooperative transmission is an emerging wireless communication technique that improves wireless channel capacity through multiuser cooperation in the physical layer. It is expected to have a profound impact on network performance and design. However, cooperative transmission can be vulnerable to selfish behaviors and malicious attacks, especially in its current design. In this paper, we investigate two fundamental questions Does cooperative transmission provide new opportunities to malicious parties to undermine the network performance? Are there new ways to defend wireless networks through physical layer cooperation? Particularly, we study the security vulnerabilities of the traditional cooperative transmission schemes and show the performance degradation resulting from the misbehaviors of relay nodes. Then, we design a trust-assisted cooperative scheme that can detect attacks and has self-healing capability. The proposed scheme performs much better than the traditional schemes when there are malicious/selfish nodes or severe channel estimation errors. Finally, we investigate the advantage of cooperative transmission in terms of defending against jamming attacks. A reduction in link outage probability is achieved

Social comparison based relaying in device-to-device networks

Device-to-device (D2D) communications are recognized as a key component of future wireless networks which will help to improve spectral efficiency and network densification simultaneously. In order to guarantee a quality of service (QoS) to the cellular links, the transmit power of the D2D nodes needs to be restricted, which has lead to a poor link quality over D2D transmission. One viable option to improve the D2D link quality is incorporating cooperative relays into D2D networks. However most of the existing published work in relay assisted D2D networks has assumed that relay nodes cooperate spontaneously. This cannot always be guaranteed and we take this into account by considering a fundamental model on which donation-based cooperation depends. In par- ticular we model relay cooperation as a donation game based on social comparison and characterize cooperation probability in an evolutionary context. When applying this model we evaluate the outage and capacity of relay assisted D2D network using a stochastic geometric framework

Community Networks and Sustainability: a Survey of Perceptions, Practices, and Proposed Solutions

Community network (CN) initiatives have been around for roughly two decades, evangelizing a distinctly different paradigm for building, maintaining, and sharing network infrastructure but also defending the basic human right to Internet access. Over this time they have evolved into a mosaic of systems that vary widely with respect to their network technologies, their offered services, their organizational structure, and the way they position themselves in the overall telecommunications’ ecosystem. Common to all these highly differentiated initiatives is the sustainability challenge. We approach sustainability as a broad term with an economical, political, and cultural context. We first review the different perceptions of the term. These vary both across and within the different types of stakeholders involved in CNs and are reflected in their motivation to join such initiatives. Then, we study the diverse approaches of CN operators towards the sustainability goal. Given the rich context of the term, these range all the way from mechanisms to fund their activities, to organizational structures and social activities serving as incentives for the engagement of their members. We iterate on incentive mechanisms that have been proposed and theoretically analyzed in the literature for CNs as well as tools and processes that have been actually implemented in them. Finally, we enumerate lessons that have been learned out of these two decades of CNs’ operation and discuss additional technological and regulatory issues that are key to their longer-term sustainability

Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review

Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the network’s functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze 11 literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanism’s data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources

Optimising Cooperative Spectrum Sensing in Cognitive Radio Networks Using Interference Alignment and Space-Time Coding

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR’s) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA’s ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR’s ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input–multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU’s unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU’s receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates

Intrusion Detection for Mobile Ad Hoc Networks Based on Node Reputation

The mobile ad hoc network (MANET) is more vulnerable to attacks than traditional networks, due to the high mobility of nodes, the weakness of transmission media and the absence of central node. To overcome the vulnerability, this paper mainly studies the way to detect selfish nodes in the MANET, and thus prevent network intrusion. Specifically, a data-driven reputation evaluation model was proposed to detect selfish nodes using a new reputation mechanism. The mechanism consists of a monitoring module, a reputation evaluation module, penalty module and a response module. The MANET integrated with our reputation mechanism was compared with the traditional MANET through simulation. The results show that the addition of reputation mechanism can suppress the selfish behavior of network nodes and enhance network security