Joint Head Selection and Airtime Allocation for Data Dissemination in Mobile Social Networks

Mobile social networks (MSNs) enable people with similar interests to interact without Internet access. By forming a temporary group, users can disseminate their data to other interested users in proximity with short-range communication technologies. However, due to user mobility, airtime available for users in the same group to disseminate data is limited. In addition, for practical consideration, a star network topology among users in the group is expected. For the former, unfair airtime allocation among the users will undermine their willingness to participate in MSNs. For the latter, a group head is required to connect other users. These two problems have to be properly addressed to enable real implementation and adoption of MSNs. To this aim, we propose a Nash bargaining-based joint head selection and airtime allocation scheme for data dissemination within the group. Specifically, the bargaining game of joint head selection and airtime allocation is first formulated. Then, Nash bargaining solution (NBS) based optimization problems are proposed for a homogeneous case and a more general heterogeneous case. For both cases, the existence of solution to the optimization problem is proved, which guarantees Pareto optimality and proportional fairness. Next, an algorithm, allowing distributed implementation, for join head selection and airtime allocation is introduced. Finally, numerical results are presented to evaluate the performance, validate intuitions and derive insights of the proposed scheme

Self organization of tilts in relay enhanced networks: a distributed solution

Despite years of physical-layer research, the capacity enhancement potential of relays is limited by the additional spectrum required for Base Station (BS)-Relay Station (RS) links. This paper presents a novel distributed solution by exploiting a system level perspective instead. Building on a realistic system model with impromptu RS deployments, we develop an analytical framework for tilt optimization that can dynamically maximize spectral efficiency of both the BS-RS and BS-user links in an online manner. To obtain a distributed self-organizing solution, the large scale system-wide optimization problem is decomposed into local small scale subproblems by applying the design principles of self-organization in biological systems. The local subproblems are non-convex, but having a very small scale, can be solved via standard nonlinear optimization techniques such as sequential quadratic programming. The performance of the developed solution is evaluated through extensive simulations for an LTE-A type system and compared against a number of benchmarks including a centralized solution obtained via brute force, that also gives an upper bound to assess the optimality gap. Results show that the proposed solution can enhance average spectral efficiency by up to 50% compared to fixed tilting, with negligible signaling overheads. The key advantage of the proposed solution is its potential for autonomous and distributed implementation

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Resource Allocation in Relay Enhanced Broadband Wireless Access Networks

The use of relay nodes to improve the performance of broadband wireless access (BWA) networks has been the subject of intense research activities in recent years. Relay enhanced BWA networks are anticipated to support multimedia traffic (i.e., voice, video, and data traffic). In order to guarantee service to network users, efficient resource distribution is imperative. Wireless multihop networks are characterized by two inherent dynamic characteristics: 1) the existence of wireless interference and 2) mobility of user nodes. Both mobility and interference greatly influence the ability of users to obtain the necessary resources for service. In this dissertation we conduct a comprehensive research study on the topic of resource allocation in the presence of interference and mobility. Specifically, this dissertation investigates the impact interference and mobility have on various aspects of resource allocation, ranging from fairness to spectrum utilization. We study four important resource allocation algorithms for relay enhanced BWA networks. The problems and our research achievements are briefly outlined as follows. First, we propose an interference aware rate adaptive subcarrier and power allocation algorithm using maximum multicommodity flow optimization. We consider the impact of the wireless interference constraints using Signal to Interference Noise Ratio (SINR). We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating the impact of interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution. Second, we investigate the benefits of decoupled optimization of interference aware routing and scheduling using SINR and spatial reuse to improve the overall achievable throughput. We model the routing optimization problem as a linear program using maximum concurrent flows. We develop an optimization formulation to schedule the link traffic such that interference is mitigated and time slots are reused appropriately based on spatial TDMA (STDMA). The scheduling problem is shown to be NP-hard and is solved using the column generation technique. We compare our formulations to conventional counterparts in the literature and show that our approach guarantees higher throughput by mitigating the effect of interference effectively. Third, we investigate the problem of multipath flow routing and fair bandwidth allocation under interference constraints for multihop wireless networks. We first develop a novel isotonic routing metric, RI3M, considering the influence of interflow and intraflow interference. Second, in order to ensure QoS, an interference-aware max-min fair bandwidth allocation algorithm, LMX:M3F, is proposed where the lexicographically largest bandwidth allocation vector is found among all optimal allocation vectors while considering constraints of interference on the flows. We compare with various interference based routing metrics and interference aware bandwidth allocation algorithms established in the literature to show that RI3M and LMX:M3F succeed in improving network performance in terms of delay, packet loss ratio and bandwidth usage. Lastly, we develop a user mobility prediction model using the Hidden Markov Model(HMM) in which prediction control is transferred to the various fixed relay nodes in the network. Given the HMM prediction model, we develop a routing protocol which uses the location information of the mobile user to determine the interference level on links in its surrounding neighborhood. We use SINR as the routing metric to calculate the interference on a specific link (link cost). We minimize the total cost of routing as a cost function of SINR while guaranteeing that the load on each link does not exceed its capacity. The routing protocol is formulated and solved as a minimum cost flow optimization problem. We compare our SINR based routing algorithm with conventional counterparts in the literature and show that our algorithm reinforces routing paths with high link quality and low latency, therefore improving overall system throughput. The research solutions obtained in this dissertation improve the service reliability and QoS assurance of emerging BWA networks