Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints

This work proposes a distributed power allocation scheme for maximizing energy efficiency in the uplink of orthogonal frequency-division multiple access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs) in the network are modeled as rational agents that engage in a non-cooperative game where each UE allocates its available transmit power over the set of assigned subcarriers so as to maximize its individual utility (defined as the user's throughput per Watt of transmit power) subject to minimum-rate constraints. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of Nash equilibrium which accounts for the case where an agent's set of possible actions depends on the actions of its opponents. Since the problem at hand might not be feasible, Debreu equilibria do not always exist. However, using techniques from fractional programming, we provide a characterization of equilibrial power allocation profiles when they do exist. In particular, Debreu equilibria are found to be the fixed points of a water-filling best response operator whose water level is a function of minimum rate constraints and circuit power. Moreover, we also describe a set of sufficient conditions for the existence and uniqueness of Debreu equilibria exploiting the contraction properties of the best response operator. This analysis provides the necessary tools to derive a power allocation scheme that steers the network to equilibrium in an iterative and distributed manner without the need for any centralized processing. Numerical simulations are then used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu

Base station cooperation in multiple input multiple output orthogonal frequency division multiple access systems

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2009.Thesis (Master's) -- Bilkent University, 2009.Includes bibliographical references leaves 60-62.Newly emerging advancements such as multiple input multiple output (MIMO) and orthogonal frequency division multiple access (OFDMA) techniques become indispensable parts of today’s wireless systems such as WiMAX (IEEE 802.16 standard) since they can increase the supportable data rates significantly. However, achieving the maximum spectral efficiency in a MIMO system requires perfect channel state information (CSI) at the transmitter side and multicarrier nature of OFDMA systems increase the necessary CSI feedback from users to base stations remarkably. To further increase the supportable data rates, using frequency reuse factor of 1 in the system is also mandatory. Unfortunately, this results in significant cochannel interference (CCI) observed especially by the users near cell edges, which can severely degrade the system spectral efficiency. To cope with this problem, base station cooperation may play an important role. In this thesis, the problem of cooperative data transmission from base stations to users in multicellular MIMO-OFDMA systems is considered. An efficient cooperative scheduling and data transmission scheme, requiring limited CSI feedback from users to base stations and also limited information exchange between the base stations, is proposed. The numerical results demonstrate that, the proposed algorithm offers considerable spectral efficiency gains compared to conventional frequency reuse and noncooperative schemes, under severe CCI conditionsTokel, Turgut BarışM.S

Resource allocation in networks via coalitional games

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) wireless networks and in smart power grids by casting the problems to the coalitional game framework and by providing a constructive iterative algorithm based on dynamic learning theory.  Software Engineering (Software)Algorithms and the Foundations of Software technolog

Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

Resource allocation (RA) techniques should be made efficient and optimized in order to enhance the QoS (power & bit, capacity, scalability) of high-speed networking data applications. This research attempts to further increase the efficiency towards near-optimal performance. RA’s problem involves assignment of subcarriers, power and bit amounts for each user efficiently. Several studies conducted by the Federal Communication Commission have proven that conventional RA approaches are becoming insufficient for rapid demand in networking resulted in spectrum underutilization, low capacity and convergence, also low performance of bit error rate, delay of channel feedback, weak scalability as well as computational complexity make real-time solutions intractable. Mainly due to sophisticated, restrictive constraints, multi-objectives, unfairness, channel noise, also unrealistic when assume perfect channel state is available. The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). Thus, a modified SFLA is introduced and integrated in Orthogonal Frequency Division Multiplexing (OFDM) system. Then SFLA generated random population of solutions (power, bit), the fitness of each solution is calculated and improved for each subcarrier and user. The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. The proposed algorithm managed to offer fastest convergence given that the number of iterations required to get to the 0.001% error of the global optimum is 75 compared to 92 in the conventional techniques. Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are propose

Adaptive radio resource management schemes for the downlink of the OFDMA-based wireless communication systems

Includes bibliographical references.Due to its superior characteristics that make it suitable for high speed mobile wireless systems OFDMA has been adopted by next generation broadband wireless standards including Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution – Advanced (LTE-A). Intelligent and adaptive Radio Resource Management (RRM) schemes are a fundamental tool in the design of wireless systems to be able to fully and efficiently utilize the available scarce resources and be able to meet the user data rates and QoS requirements. Previous works were only concerned with maximizing system efficiency and thus used opportunistic algorithms that allocate resources to users with the best opportunities to optimize system capacity. Thus, only those users with good channel conditions were considered for resource allocation and users in bad channel conditions were left out to starve of resources. The main objective of our study is to design adaptive radio resource allocation (RRA) algorithms that distribute the scarce resources more fairly among network users while efficiently using the resources to maximize system throughput. Four scheduling algorithms have been formulated and analysed based on fairness, throughputs and delay. This was done for users demanding different services and QoS requirements. Two of the scheduling algorithms, Maximum Sum Rate (MSR) and Round Robin (RR) are used respectively, as references to analyze throughput and fairness among network users. The other two algorithms are Proportional Fair Scheduling (PFS) and Margin Adaptive Scheduling Scheme (MASS)

Advanced Techniques for Future Multicarrier Systems

Future multicarrier systems face the tough challenge of supporting high data-rate and high-quality services. The main limitation is the frequency-selective nature of the propagation channel that affects the received signal, thus degrading the system performance. OFDM can be envisaged as one of the most promising modulation techniques for future communication systems. It exhibits robustness to ISI even in very dispersive environments and its main characteristic is to take advantage of channel diversity by performing dynamic resource allocation. In a multi-user OFDMA scenario, the challenge is to allocate, on the basis of the channel knowledge, different portions of the available frequency spectrum among the users in the systems. Literature on resource allocation for OFDMA systems mainly focused on single-cell systems, where the objective is to assign subcarriers, power and data-rate for each user according to a predetermined criterion. The problem can be formulated with the goal of either maximizing the system sum-rate subject to a constraint on transmitted power or minimizing the overall power consumption under some predetermined constraints on rate per user. Only recently, literature focuses on resource allocation in multi-cell networks, where the goal is not only to take advantage of frequency and multi-user diversity, but also to mitigate MAI, which represents one of the most limiting factor for such problems. We consider a multi-cell OFDMA system with frequency reuse distance equal to one. Allowing all cells to transmit on the whole bandwidth unveils large potential gains in terms of spectral efficiency in comparison with conventional cellular systems. Such a scenario, however, is often deemed unfeasible because of the strong MAI that negatively affects the system performance. In this dissertation we present a layered architecture that integrates a packet scheduler with an adaptive resource allocator, explicitly designed to take care of the multiple access interference. Each cell performs its resource management in a distributed way without any central controller. Iterative resource allocation assigns radio channels to the users so as to minimize the interference. Packet scheduling guarantees that all users get a fair share of resources regardless of their position in the cell. This scheduler-allocator architecture integrates both goals and is able to self adapt to any traffic and user configuration. An adaptive, distributed load control strategy can reduce the cell load so that the iterative procedure always converges to a stable allocation, regardless of the interference. Numerical results show that the proposed architecture guarantees both high spectral efficiency and throughput fairness among flows. In the second part of this dissertation we deal with FBMC communication systems. FBMC modulation is a valid alternative to conventional OFDM signaling as it presents a set of appealing characteristics, such as robustness to narrowband interferers, more flexibility to allocate groups of subchannels to different users/services, and frequency-domain equalization without any cyclic extension. However, like any other multicarrier modulations, FBMC is strongly affected by residual CFOs that have to be accurately estimated. Unlike previously proposed algorithms, whereby frequency is recovered either relying on known pilot symbols multiplexed with the data stream or exploiting specific properties of the multicarrier signal structure following a blind approach, we present and discuss an algorithm based on the ML principle, which takes advantage both of pilot symbols and also indirectly of data symbols through knowledge and exploitation of their specific modulation format. The algorithm requires the availability of the statistical properties of channel fading up to second-order moments. It is shown that the above approach allows to improve on both frequency acquisition range and estimation accuracy of previously published schemes

Opportunities and Challenges in OFDMA-Based Cellular Relay Networks: A Radio Resource Management Perspective

The opportunities and flexibility in relay networks and orthogonal frequency-division multiple access (OFDMA) make the combination a suitable candidate network and air-interface technology for providing reliable and ubiquitous high-data-r

Distributed energy-aware resource allocation in multi-antenna multi-carrier interference networks with statistical CSI

Resource allocation for energy efficiency optimization in multi-carrier interference networks with multiple receive antennas is tackled. First, a one-hop network is considered, and then, the results are extended to the case of a two-hop network in which amplify-and-forward relaying is employed to enable communication. A distributed algorithm which optimizes a system-wide energy-efficient performance function, and which is guaranteed to converge to a stable equilibrium point, is provided. Unlike most previous works, in the definition of the energy efficiency, not only the users' transmit power but also the circuit power that is required to operate the devices is taken into account. All of the proposed procedures are guaranteed to converge and only require statistical channel state information, thus lending themselves to a distributed implementation. The asymptotic regime of a saturated network in which both the active users and the number of receive antennas deployed in each receiver grow large is also analyzed. Numerical results are provided to confirm the merits of the proposed algorithms

Novel Intercell Interference Mitigation Algorithms for Multicell OFDMA Systems with Limited Base Station Cooperation

Resource allocation in multicell downlink orthogonal frequency division multiple-access (OFDMA) systems is investigated, where BSs first independently carry out subcarrier-allocation and then mitigate intercell interference (InterCI) with the aid of very limited base station (BS) cooperation. Two novel InterCI mitigation algorithms are proposed. The first one is the distributed decision making assisted cooperation (DDMC) algorithm, and the second one is the centralized decision making assisted cooperation (CDMC) algorithm. When employing the DDMC algorithm, each BS independently makes the InterCI mitigation decisions. By contrast, when employing the CDMC algorithm, the centralized InterCI mitigation decisions are made with the aid of the cell-edge users’ discrete InterCI information sharing among BSs. While both the algorithms motivate to maximize the spectral-efficiency (sum rate), the CDMC algorithm also aims to maximize the frequency reuse factor. In this paper, we study and compare the performance, including spectral-efficiency of cell-edge users, frequency reuse factor, overhead, etc., of the multicell downlink OFDMA systems employing the proposed and other InterCI mitigation algorithms. Our studies show that both the DDMC and CDMC algorithms can achieve better spectral-efficiency performance than the existing on-off power (OOP) algorithm. Moreover, the CDMC algorithm is capable of achieving the performance close to the upper-bound attained by the so-called full InterCI information assisted decision making (FIIDM) algorithm, which uses exhaustive search to determine the InterCI mitigation decisions. Additionally, the CDMC algorithm is demonstrated to have the highest frequency reuse factor in addition to its spectral-efficiency advantage