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

Channel and queue aware joint relay selection and resource allocation for MISO-OFDMA based user-relay assisted cellular networks

User-relay assisted orthogonal frequency division multiple access (OFDMA) networks are cost-effective solutions to meet the growing capacity and coverage demands of the next generation cellular networks. These networks can be used with multiple antennas technology in order to obtain a diversity gain to combat signal fading and to obtain more capacity gain without increasing the bandwidth or transmit power. Efficient relay selection and resource allocation are crucial in such a multi-user, multi-relay and multi-antenna environment to fully exploit the benefits of the combination of user-relaying and multiple antennas technology. Thus, we propose a channel and queue aware joint relay selection and resource allocation algorithm for multiple-input single-output (MISO)-OFDMA based user-relay assisted downlink cellular networks. Since, the proposed algorithm is not only channel but also queue-aware, the system resources are allocated efficiently among the users. The proposed algorithm for the MISO-OFDMA based user-relay assisted scheme is compared to existing MISO-OFDMA based non-relaying and fixed relay assisted schemes and it is also compared with the existing single-input single-output (SISO)-OFDMA based user-relay assisted scheme. Simulation results revealed that the proposed scheme outperforms the existing schemes in terms of cell-edge users’ total data rate, average backlog and average delay

Energy and computationally efficient resource allocation methods for cellular relay-aided networks with system stability consideration

The increasing demand for coverage extension and power gain, along with the need for decreasing implementation costs, raised the idea of relaying cellular systems. Developing relay stations as a coverage extension and low cost mechanism has also brought up the challenge of utilizing the available network resources cooperatively between base stations and relays. The topic of resource allocation in the downlink of a relaying cellular system is studied in the current dissertation with the objective of maximizing transmission rate, encompassing system stability and managing the interference as it has not been investigated as a comprehensive allocation problem in the previous literature. We begin our study by modeling a single cell downlink transmission system with the objective to enhance the throughput of cell-edge users by employing decode-and-forward relay stations. We study the queue length evolution at each hop and propose a rate control mechanism to stabilize the considered queues. Accordingly, we propose a novel allocation model which maximizes user throughput with respect to the channel condition and the stability requirements. To solve the proposed allocation problem, we introduced optimization algorithm as well as heuristic approaches which offer low computation complexity. Next, we enhance the initial allocation method by considering a multi-cell system that accounts for more general and practical cellular networks. The multi-cell model embodies extra constraints for controlling the interference to the users of neighboring cells. We propose a different set of stability constraints which do not enquire a priori knowledge of the statistics of the arriving traffic. In an approach to improve the energy efficiency while respecting the stability and interference criteria, we also suggest an energy-conservative allocation scheme. We solve the defined allocation problems in a central controlling system. As our final contribution, we enhance the proposed multi-cell allocation model with a low overhead and distributed approach. The proposed method is based on the idea of dividing the resource allocation task between each base station and its connected relay stations. In addition, the messaging overhead for controlling inter-cell interference is minimized using the reference-station method. This distributed approach offers high degree of energy efficiency as well as more scalability in comparison to centralized schemes, when the system consists of larger number of cells and users. Since the defined problems embody multiple variables and constraints, we develop a framework to cast the joint design in the optimization form which gives rise to nonlinear and nonconvex problems. In this regard, we employ time-sharing technique to tackle the combinatorial format of the allocation problem. In addition, it is important to consider the situation that the time-shared approach is not beneficial when subcarriers are not allowed to be shared during one time-slot. To overcome this obstacle, we apply heuristic algorithms as well as convex optimization techniques to obtain exclusive subcarrier allocation schemes. To evaluate the performance of the proposed solutions, we compare them in terms of the achieved throughput, transmitted power, queue stability, feedback overhead, and computation complexity. By the means of extensive simulation scenarios as well as numerical analysis, we demonstrate the remarkable advantages of the suggested approaches. The results of the present dissertation are appealing for designing of future HetNet systems specifically when the communication latency and the energy consumption are required to be minimized

Relay assisted device-to-device communication with channel uncertainty

The gains of direct communication between user equipment in a network may not be fully realised due to the separation between the user equipment and due to the fading that the channel between these user equipment experiences. In order to fully realise the gains that direct (device-to-device) communication promises, idle user equipment can be exploited to serve as relays to enforce device-to-device communication. The availability of potential relay user equipment creates a problem: a way to select the relay user equipment. Moreover, unlike infrastructure relays, user equipment are carried around by people and these users are self-interested. Thus the problem of relay selection goes beyond choosing which device to assist in relayed communication but catering for user self-interest. Another problem in wireless communication is the unavailability of perfect channel state information. This reality creates uncertainty in the channel and so in designing selection algorithms, channel uncertainty awareness needs to be a consideration. Therefore the work in this thesis considers the design of relay user equipment selection algorithms that are not only device centric but that are relay user equipment centric. Furthermore, the designed algorithms are channel uncertainty aware. Firstly, a stable matching based relay user equipment selection algorithm is put forward for underlay device-to-device communication. A channel uncertainty aware approach is proposed to cater to imperfect channel state information at the devices. The algorithm is combined with a rate based mode selection algorithm. Next, to cater to the queue state at the relay user equipment, a cross-layer selection algorithm is proposed for a twoway decode and forward relay set up. The algorithm proposed employs deterministic uncertainty constraint in the interference channel, solving the selection algorithm in a heuristic fashion. Then a cluster head selection algorithm is proposed for device-to-device group communication constrained by channel uncertainty in the interference channel. The formulated rate maximization problem is solved for deterministic and probabilistic constraint scenarios, and the problem extended to a multiple-input single-out scenario for which robust beamforming was designed. Finally, relay utility and social distance based selection algorithms are proposed for full duplex decode and forward device-to-device communication set up. A worst-case approach is proposed for a full channel uncertainty scenario. The results from computer simulations indicate that the proposed algorithms offer spectral efficiency, fairness and energy efficiency gains. The results also showed clearly the deterioration in the performance of networks when perfect channel state information is assumed

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Efficient and Secure Resource Allocation in Mobile Edge Computing Enabled Wireless Networks

To support emerging applications such as autonomous vehicles and smart homes and to build an intelligent society, the next-generation internet of things (IoT) is calling for up to 50 billion devices connected world wide. Massive devices connection, explosive data circulation, and colossal data processing demand are driving both the industry and academia to explore new solutions. Uploading this vast amount of data to the cloud center for processing will significantly increase the load on backbone networks and cause relatively long latency to time-sensitive applications. A practical solution is to deploy the computing resource closer to end-users to process the distributed data. Hence, Mobile Edge Computing (MEC) emerged as a promising solution to providing high-speed data processing service with low latency. However, the implementation of MEC networks is handicapped by various challenges. For one thing, to serve massive IoT devices, dense deployment of edge servers will consume much more energy. For another, uploading sensitive user data through a wireless link intro-duces potential risks, especially for those size-limited IoT devices that cannot implement complicated encryption techniques. This dissertation investigates problems related to Energy Efficiency (EE) and Physical Layer Security (PLS) in MEC-enabled IoT networks and how Non-Orthogonal Multiple Access (NOMA), prediction-based server coordination, and Intelligent Reflecting Surface (IRS) can be used to mitigate them. Employing a new spectrum access method can help achieve greater speed with less power consumption, therefore increasing system EE. We first investigated NOMA-assisted MEC networks and verified that the EE performance could be significantly improved. Idle servers can consume unnecessary power. Proactive server coordination can help relieve the tension of increased energy consumption in MEC systems. Our next step was to employ advanced machine learning algorithms to predict data workload at the server end and adaptively adjust the system configuration over time, thus reducing the accumulated system cost. We then introduced the PLS to our system and investigated the long-term secure EE performance of the MEC-enabled IoT network with NOMA assistance. It has shown that NOMA can improve both EE and PLS for the network. Finally, we switch from the single antenna scenario to a multiple-input single-output (MISO) system to exploit space diversity and beam forming techniques in mmWave communication. IRS can be used simultaneously to help relieve the pathloss and reconfigure multi-path links. In the final part, we first investigated the secure EE performance of IRS-assisted MISO networks and introduced a friendly jammer to block the eavesdroppers and improve the PLS rate. We then combined the IRS with the NOMA in the MEC network and showed that the IRS can further enhance the system EE

무선통신망에서 처리율 개선을 위한 신호전달 부하의 저감에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 전화숙.무선통신망(wireless networks)은 무선 채널의 상태 변화에 따른 성능 저하를 줄이기 위해 링크 적응(link adaptation) 기술을 기본적으로 사용한다. 링크 적응 기술을 위해서는 채널 상태 정보를 추정하고 수집해야하기 때문에 이에 따른 신호전달 부하(signaling overhead)가 발생하게 된다. 본 논문에서는 무선통신망에서의 신호전달 부하를 줄이기 위한 두 가지 기법을 제안하였다. 먼저 협력 통신 네트워크(cooperative communication networks)에서의 적응적인 전송 기법을 제안하였다. 제안한 기법을 사용하는 협력 통신 네트워크는 ACK(positive acknowledgement)/NACK(negative ACK)와 같은 제한된 피드백 정보로부터 추정된 채널 상태에 기반을 두어 전송 속도를 조절하면서 릴레이(relay)의 사용여부도 함께 결정한다. 제한된 피드백 정보는 실제 채널 상태에 대한 부분적인 정보만을 제공하기 때문에 제안하는 기법을 불확실성 마코브 의사 결정(partially observable Markov decision process)에 따라 설계하였다. 다음으로, 셀룰러 네트워크에서의 기기 간(D2D, device-to-device) 통신을 위한 자원 관리 기법을 제안하였다. 제안한 기법은 두 단계로 구성되고 준 분산적(semi-distributed)으로 동작한다. 첫 번째 단계에서는 중앙 집중적(centralized)으로 기지국이 자원 블록을 B2D(BS-to-user device) 링크와 D2D 링크에게 할당한다. 두 번째 단계에서는 분산적(distributed)으로 기지국은 B2D 링크에 할당된 자원 블록들을 사용하여 전송 스케줄을 결정(scheduling)하고, 각 D2D 링크의 제 1 사용자 기기(primary user device)는 해당 D2D 링크에 할당된 자원 블록들에서의 링크 적응을 수행한다. 이러한 자원 관리 구조는 중앙 집중적 기법처럼 높은 네트워크 용량을 달성할 뿐 아니라 분산적 기법처럼 낮은 신호전달 및 계산(computational) 부하를 필요로 한다. 본 논문에서는 제안한 자원 관리 구조에서 주파수 자원 효율을 최대화하는 자원 블록 할당 문제들을 두 가지 서로 다른 자원 할당 정책에 대하여 만들고 이 문제들을 풀기 위해 탐욕(greedy) 알고리즘과 열 추가 기반(column generation-based) 알고리즘을 제안하였다. 또한 시뮬레이션을 통해 제안하는 기법들이 설계 목표를 달성하고 기존의 기법보다 높은 성능을 보이면서도 신호전달 부하를 줄일 수 있음을 보였다.Wireless networks usually adopt some link adaptation techniques to mitigate the performance degradation due to the time-varying characteristics of wireless channels. Since the link adaptation techniques require to estimate and collect channel state information, signaling overhead is inevitable in wireless networks. In this thesis, we propose two schemes to reduce the signaling overhead in wireless networks. First, we design an adaptive transmission scheme for cooperative communication networks. The cooperative network with the proposed scheme chooses the transmission rate and decides to involve the relay in transmission, adapting to the channel state estimated from limited feedback information (e.g., ACK/NACK feedback). Considering that the limited feedback information provides only partial knowledge about the actual channel states, we design a decision-making algorithm on cooperative transmission by using a partially observable Markov decision process (POMDP) framework. Next, we also propose a two-stage semi-distributed resource management framework for the device-to-device (D2D) communication in cellular networks. At the first stage of the framework, the base station (BS) allocates resource blocks (RBs) to BS-to-user device (B2D) links and D2D links, in a centralized manner. At the second stage, the BS schedules the transmission using the RBs allocated to B2D links, while the primary user device of each D2D link carries out link adaptation on the RBs allocated to the D2D link, in a distributed fashion. The proposed framework has the advantages of both centralized and distributed design approaches, i.e., high network capacity and low signaling/computational overhead, respectively. We formulate the problems of RB allocation to maximize the radio resources efficiency, taking account of two different policies on the spatial reuse of RBs. To solve these problems, we suggest a greedy algorithm and a column generation-based algorithm. By simulation, it is shown that the proposed schemes achieve their design goal properly and outperform existing schemes while reducing the signaling overhead.1 Introduction 1 1.1 Background and Motivation 1 1.2 Approaches to Reduce Signaling Overhead 5 1.3 Proposed Schemes 7 1.3.1 Adaptive Transmission Scheme for Cooperative Communication 7 1.3.2 Resource Management Scheme for D2D Communication in Cellular Networks 8 1.4 Organization 10 2 Adaptive Transmission Scheme for Cooperative Communication 11 2.1 System Model 11 2.2 Cooperative Networks with Limited Feedback 12 2.2.1 Operation of the Proposed Cooperative Network 12 2.2.2 Finite-State Markov Channel Model 15 2.2.3 Packet Error Probability 16 2.2.4 Channel Feedback Schemes 18 2.3 Adaptive Transmission Scheme for Cooperative Communication 19 2.3.1 POMDP Formulation 19 2.3.2 Solution to POMDP 22 3 Resource Management Scheme for D2D Communication in Cellular Networks 25 3.1 System Model 25 3.1.1 Network Model 25 3.1.2 Radio Resource Model 27 3.2 Proposed Resource Management Framework 28 3.2.1 Framework Overview 28 3.2.2 Two-Stage Resource Management 29 3.2.3 Advantages of the Proposed Framework 31 3.3 Conditions for Simultaneous Transmission of B2D and D2D Links 33 3.3.1 Analysis of Interference on B2D and D2D Links 33 3.3.2 Conditions for Simultaneous Transmission of B2D and D2D Links 36 3.4 Resource Block Allocation 38 3.4.1 Resource Block Allocation with Conservative Reuse Policy 39 3.4.2 Resource Block Allocation with Aggressive Reuse Policy 44 4 Performance Evaluation 52 4.1 Adaptive Transmission Scheme for Cooperative Communication 52 4.1.1 Simulation Model 52 4.1.2 Simulation Results 53 4.2 Resource Management Scheme for D2D Communication in Cellular Networks 62 4.2.1 Simulation Model 62 4.2.2 Simulation Results 64 5 Conclusion 75 Bibliography 77 Abstract 85Docto

Energy-efficient cooperative resource allocation for OFDMA

Energy is increasingly becoming an exclusive commodity in next generation wireless communication systems, where even in legacy systems, the mobile operators operational expenditure is largely attributed to the energy bill. However, as the amount of mobile traffic is expected to double over the next decade as we enter the Next Generation communications era, the need to address energy efficient protocols will be a priority. Therefore, we will need to revisit the design of the mobile network in order to adopt a proactive stance towards reducing the energy consumption of the network. Future emerging communication paradigms will evolve towards Next Generation mobile networks, that will not only consider a new air interface for high broadband connectivity, but will also integrate legacy communications (LTE/LTE-A, IEEE 802.11x, among others) networks to provide a ubiquitous communication platform, and one that can host a multitude of rich services and applications. In this context, one can say that the radio access network will predominantly be OFDMA based, providing the impetus for further research studies on how this technology can be further optimized towards energy efficiency. In fact, advanced approaches towards both energy and spectral efficient design will still dominate the research agenda. Taking a step towards this direction, LTE/LTE-A (Long Term Evolution-Advanced) have already investigated cooperative paradigms such as SON (self-Organizing Networks), Network Sharing, and CoMP (Coordinated Multipoint) transmission. Although these technologies have provided promising results, some are still in their infancy and lack an interdisciplinary design approach limiting their potential gain. In this thesis, we aim to advance these future emerging paradigms from a resource allocation perspective on two accounts. In the first scenario, we address the challenge of load balancing (LB) in OFDMA networks, that is employed to redistribute the traffic load in the network to effectively use spectral resources throughout the day. We aim to reengineer the load-balancing (LB) approach through interdisciplinary design to develop an integrated energy efficient solution based on SON and network sharing, what we refer to as SO-LB (Self-Organizing Load balancing). Obtained simulation results show that by employing SO-LB algorithm in a shared network, it is possible to achieve up to 15-20% savings in energy consumption when compared to LTE-A non-shared networks. The second approach considers CoMP transmission, that is currently used to enhance cell coverage and capacity at cell edge. Legacy approaches mainly consider fundamental scheduling policies towards assigning users for CoMP transmission. We build on these scheduling approaches towards a cross-layer design that provide enhanced resource utilization, fairness, and energy saving whilst maintaining low complexity, in particular for broadband applications