Non-cooperative Feedback Rate Control Game for Channel State Information in Wireless Networks

It has been well recognized that channel state information (CSI) feedback is of great importance for dowlink transmissions of closed-loop wireless networks. However, the existing work typically researched the CSI feedback problem for each individual mobile station (MS), and thus, cannot efficiently model the interactions among self-interested mobile users in the network level. To this end, in this paper, we propose an alternative approach to investigate the CSI feedback rate control problem in the analytical setting of a game theoretic framework, in which a multiple-antenna base station (BS) communicates with a number of co-channel MSs through linear precoder. Specifically, we first present a non-cooperative feedback-rate control game (NFC), in which each MS selects the feedback rate to maximize its performance in a distributed way. To improve efficiency from a social optimum point of view, we then introduce pricing, called the non-cooperative feedback-rate control game with price (NFCP). The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback rate. The existence of the Nash equilibrium of such games is investigated, and two types of feedback protocols (FDMA and CSMA) are studied. Simulation results show that by adjusting the pricing factor, the distributed NFCP game results in close optimal performance compared with that of the centralized scheme.Comment: 26 pages, 10 figures; IEEE Journal on Selected Areas in Communications, special issue on Game Theory in Wireless Communications, 201

Cross-layer scheduling and resource allocation for heterogeneous traffic in 3G LTE

3G long term evolution (LTE) introduces stringent needs in order to provide different kinds of traffic with Quality of Service (QoS) characteristics. The major problem with this nature of LTE is that it does not have any paradigm scheduling algorithm that will ideally control the assignment of resources which in turn will improve the user satisfaction. This has become an open subject and different scheduling algorithms have been proposed which are quite challenging and complex. To address this issue, in this paper, we investigate how our proposed algorithm improves the user satisfaction for heterogeneous traffic, that is, best-effort traffic such as file transfer protocol (FTP) and real-time traffic such as voice over internet protocol (VoIP). Our proposed algorithm is formulated using the cross-layer technique. The goal of our proposed algorithm is to maximize the expected total user satisfaction (total-utility) under different constraints. We compared our proposed algorithm with proportional fair (PF), exponential proportional fair (EXP-PF), and U-delay. Using simulations, our proposed algorithm improved the performance of real-time traffic based on throughput, VoIP delay, and VoIP packet loss ratio metrics while PF improved the performance of best-effort traffic based on FTP traffic received, FTP packet loss ratio, and FTP throughput metrics

EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks

This paper addresses the cell association problem in the downlink of a multi-tier heterogeneous network (HetNet), where base stations (BSs) have finite number of resource blocks (RBs) available to distribute among their associated users. Two problems are defined and treated in this paper: sum utility of long term rate maximization with long term rate quality of service (QoS) constraints, and global outage probability minimization with outage QoS constraints. The first problem is well-suited for low mobility environments, while the second problem provides a framework to deal with environments with fast fading. The defined optimization problems in this paper are solved in two phases: cell association phase followed by the optional RB distribution phase. We show that the cell association phase of both problems have the same structure. Based on this similarity, we propose a unified distributed algorithm with low levels of message passing to for the cell association phase. This distributed algorithm is derived by relaxing the association constraints and using Lagrange dual decomposition method. In the RB distribution phase, the remaining RBs after the cell association phase are distributed among the users. Simulation results show the superiority of our distributed cell association scheme compared to schemes that are based on maximum signal to interference plus noise ratio (SINR)

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin