A Tutorial on Clique Problems in Communications and Signal Processing

Since its first use by Euler on the problem of the seven bridges of K\"onigsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and $k$-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Performance analysis of biological resource allocation algorithms for next generation networks.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF.Publications listed on page iii

Distributed optimisation techniques for wireless networks

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders

Distributed radio resource allocation in wireless heterogeneous networks

This dissertation studies the problem of resource allocation in the radio access network of heterogeneous small-cell networks (HetSNets). A HetSNet is constructed by introducing smallcells(SCs) to a geographical area that is served by a well-structured macrocell network. These SCs reuse the frequency bands of the macro-network and operate in the interference-limited region. Thus, complex radio resource allocation schemes are required to manage interference and improve spectral efficiency. Both centralized and distributed approaches have been suggested by researchers to solve this problem. This dissertation follows the distributed approach under the self-organizing networks (SONs) paradigm. In particular, it develops game-theoretic and learning-theoretic modeling, analysis, and algorithms. Even though SONs may perform subpar to a centralized optimal controller, they are highly scalable and fault-tolerant. There are many facets to the problem of wireless resource allocation. They vary by the application, solution, methodology, and resource type. Therefore, this thesis restricts the treatment to four subproblems that were chosen due to their significant impact on network performance and suitability to our interests and expertise. Game theory and mechanism design are the main tools used since they provide a sufficiently rich environment to model the SON problem. Firstly, this thesis takes into consideration the problem of uplink orthogonal channel access in a dense cluster of SCs that is deployed in a macrocell service area. Two variations of this problem are modeled as noncooperative Bayesian games and the existence of pure-Bayesian Nash symmetric equilibria are demonstrated. Secondly, this thesis presents the generalized satisfaction equilibrium (GSE) for games in satisfaction-form. Each wireless agent has a constraint to satisfy and the GSE is a mixed-strategy profile from which no unsatisfied agent can unilaterally deviate to satisfaction. The objective of the GSE is to propose an alternative equilibrium that is designed specifically to model wireless users. The existence of the GSE, its computational complexity, and its performance compared to the Nash equilibrium are discussed. Thirdly, this thesis introduces verification mechanisms for dynamic self-organization of Wireless access networks. The main focus of verification mechanisms is to replace monetary transfers that are prevalent in current research. In the wireless environment particular private information of the wireless agents, such as block error rate and application class, can be verified at the access points. This verification capability can be used to threaten false reports with backhaul throttling. The agents then learn the truthful equilibrium over time by observing the rewards and punishments. Finally, the problem of admission control in the interfering-multiple access channel with rate constraints is addressed. In the incomplete information setting, with compact convex channel power gains, the resulting Bayesian game possesses at least one pureBayesian Nash equilibrium in on-off threshold strategies. The above-summarized results of this thesis demonstrate that the HetSNets are amenable to self-organization, albeit with adapted incentives and equilibria to fit the wireless environment. Further research problems to expand these results are identified at the end of this document

이동통신 네트워크에서의 QoS 패킷 스케줄러 설계 및 고정 릴레이 관련 주파수 재사용 관리 기법 연구

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 박세웅.The main interest of this paper is to understand a basic approach to provide more efficient method to allocate radio resources in the mobile communication systems, especially in which radio resources could be allocated by both frequency and time division multiple access. So, we consider OFDMA system and the ideas described in this paper could be easily applied to the current and next generation mobile communication systems. This paper studies two basic research themesa QoS packet scheduler design and fixed relay resource management policies based on frequency reuse in mobile networks. This paper considers novel scheduler structures that are executable in the environments of multiple traffic classes and multiple frequency channels. To design a scheduler structure for multiple traffic classes, we first propose a scheduler selection rule that uses the priority of traffic class and the urgency level of each packet. Then we relax the barrier of traffic class priority when a high priority packet has some room in waiting time. This gives us a chance to exploit multiuser diversity, thereby giving more flexibility in scheduling. Our considered scheduler can achieve higher throughput compared to the simple extension of conventional modified largest weighted delay first (MLWDF) scheduler while maintaining the delay performance for QoS class traffic. We also design a scheduler structure for multiple frequency channels that chooses a good channel for each user whenever possible to exploit frequency diversity. The simulation results show that our proposed scheduler increases the total system throughput by up to 50% without degrading the delay performance. This paper also introduces radio resource management schemes based on frequency reuse for fixed relay stations in mobile cellular networks. Mobile stations in the cell boundary experience poor spectral efficiency due to the path loss and interference from adjacent cells. Therefore, satisfying QoS requirements of each MS at the cell boundary has been an important issue. To resolve this spectral efficiency problem at the cell boundary, deploying fixed relay stations has been actively considered. In this paper, we consider radio resource management policies based on frequency reuse for fixed relays that include path selection rules, frequency reuse pattern matching, and frame transmission pattern matching among cells. We evaluate performance of each policy by varying parameter values such as relay stations position and frequency reuse factor. Through Monte Carlo simulations and mathematical analysis, we suggest some optimal parameter values for each policy and discuss some implementation issues that need to be considered in practical deployment of relay stations. We also surveyed further works that many researchers have been studied to tackle the similar problems of QoS scheduling and resource management for relay with our proposed work. We expect that there would be more future works by priority-based approach and energy-aware approach for QoS scheduling. Also current trends such as the rising interest in IoT system, discussion of densification of cells and D2D communications in 5G systems make us expect that the researches in these topics related with relays would be popular in the future. We also think that there are many interesting problems regarding QoS support and resource management still waiting to be tackled, especially combined with recent key topics in mobile communication systems such as 5G standardization, AI and NFV/SDN.Chapter 1 Introduction 1 1.1 QoS Packet Scheduler 4 1.2 Fixed Relay Frequency Reuse Policies 6 Chapter 2 Scheduler Design for Multiple Traffic Classes in OFDMA Networks 10 2.1 Proposed Schedulers 10 2.1.1 Scheduler Structures 12 2.1.2 MLWDF scheduler for Multiple Traffic Classes 13 2.1.3 Joint Scheduler 13 2.2 System Model 18 2.3 Performance Evaluation 19 2.3.1 Schedulers for Multiple Traffic Classes 20 2.3.2 Impact of Scheduler Selection Rule 25 2.3.3 Frame Based Schedulers 27 2.3.4 Impact of Partial Feedback 30 2.3.5 Adaptive Threshold Version Schedulers 33 2.4 Conclusion 36 Chapter 3 Frequency Reuse Policies for Fixed Relays in Cellular Networks 40 3.1 System Model 40 3.1.1 Frame Transmission and Frequency Reuse Patterns among RSs 42 3.1.2 Positioning of RSs and Channel Capacity 44 3.1.3 Area Spectral Efficiency 45 3.2 Radio Resource Management Policies Based on Frequency Reuse 46 3.2.1 Path Selection Rule 46 3.2.2 Frequency Reuse and Frame Transmission Pattern Matchings among Cells 52 3.3 Monte Carlo Simulation and Results 53 3.4 Consideration of Practical Issues 80 3.5 Conclusion 81 Chapter 4 Surveys of Further Works 83 4.1 Further Works on QoS Schedulers 83 4.1.1 WiMAX Schedulers 85 4.1.2 LTE Schedulers 92 4.2 Further Works on Radio Resource Management in Relay Systems 98 4.3 Future Challenges 100 Chapter 5 Conclusion 104 Bibliography 107 초록 127Docto

Energy-Efficient Resource Allocation in Cloud and Fog Radio Access Networks

PhD ThesisWith the development of cloud computing, radio access networks (RAN) is migrating to fully or partially centralised architecture, such as Cloud RAN (C- RAN) or Fog RAN (F-RAN). The novel architectures are able to support new applications with the higher throughput, the higher energy e ciency and the better spectral e ciency performance. However, the more complex energy consumption features brought by these new architectures are challenging. In addition, the usage of Energy Harvesting (EH) technology and the computation o oading in novel architectures requires novel resource allocation designs.This thesis focuses on the energy e cient resource allocation for Cloud and Fog RAN networks. Firstly, a joint user association (UA) and power allocation scheme is proposed for the Heterogeneous Cloud Radio Access Networks with hybrid energy sources where Energy Harvesting technology is utilised. The optimisation problem is designed to maximise the utilisation of the renewable energy source. Through solving the proposed optimisation problem, the user association and power allocation policies are derived together to minimise the grid power consumption. Compared to the conventional UAs adopted in RANs, green power harvested by renewable energy source can be better utilised so that the grid power consumption can be greatly reduced with the proposed scheme. Secondly, a delay-aware energy e cient computation o oading scheme is proposed for the EH enabled F-RANs, where for access points (F-APs) are supported by renewable energy sources. The uneven distribution of the harvested energy brings in dynamics of the o oading design and a ects the delay experienced by users. The grid power minimisation problem is formulated. Based on the solutions derived, an energy e cient o oading decision algorithm is designed. Compared to SINR-based o oading scheme, the total grid power consumption of all F-APs can be reduced signi cantly with the proposed o oading decision algorithm while meeting the latency constraint. Thirdly, an energy-e cient computation o oading for mobile applications with shared data is investigated in a multi-user fog computing network. Taking the advantage of shared data property of latency-critical applications such as virtual reality (VR) and augmented reality (AR) into consideration, the energy minimisation problem is formulated. Then the optimal computation o oading and communications resources allocation policy is proposed which is able to minimise the overall energy consumption of mobile users and cloudlet server. Performance analysis indicates that the proposed policy outperforms other o oading schemes in terms of energy e ciency. The research works conducted in this thesis and the thorough performance analysis have revealed some insights on energy e cient resource allocation design in Cloud and Fog RANs