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

Efficient radio resource allocation scheme for 5G networks with device-to-device communication

A vital technology in the next-generation cellular network is device-to-device (D2D) communication. Cellular user enabled with D2D communication provides high spectral efficiency and further increases the coverage area of the cell, especially for the end-cell users and blind spot areas. However, the implementation of D2D communication increases interference among the cellular and D2D users. In this paper, we proposed a radio resource allocation (RRA) algorithm to manage the interference using fractional frequency reuse (FFR) scheme and Hungarian algorithm. The proposed algorithm is divided into three parts. First, the FFR scheme allocates different frequency bands among the cell (inner and outer region) for both the cellular and the D2D users to reduce the interference. Second, the Hungarian weighted bipartite matching algorithm is used to allocate the resources to D2D users with the minimum total system interference, while maintaining the total system sum rate. The cellular users share the resources with more than one D2D pair. Lastly, the local search technique of swapping is used for further allocation to minimize the interference. We implemented two types of assignments, fair multiple assignment, and restricted multiple assignment. We compared our results with existing algorithms which verified that our proposed algorithm provides outstanding results in aspects like interference reduction and system sum rate. For restricted multiple assignment, 60-70% of the D2D users are allocated in average cases

Efficient Traffic Management Algorithms for the Core Network using Device-to-Device Communication and Edge Caching

Exponentially growing number of communicating devices and the need for faster, more reliable and secure communication are becoming major challenges for current mobile communication architecture. More number of connected devices means more bandwidth and a need for higher Quality of Service (QoS) requirements, which bring new challenges in terms of resource and traffic management. Traffic offload to the edge has been introduced to tackle this demand-explosion that let the core network offload some of the contents to the edge to reduce the traffic congestion. Device-to-Device (D2D) communication and edge caching, has been proposed as promising solutions for offloading data. D2D communication refers to the communication infrastructure where the users in proximity communicate with each other directly. D2D communication improves overall spectral efficiency, however, it introduces additional interference in the system. To enable D2D communication, efficient resource allocation must be introduced in order to minimize the interference in the system and this benefits the system in terms of bandwidth efficiency. In the first part of this thesis, low complexity resource allocation algorithm using stable matching is proposed to optimally assign appropriate uplink resources to the devices in order to minimize interference among D2D and cellular users. Edge caching has recently been introduced as a modification of the caching scheme in the core network, which enables a cellular Base Station (BS) to keep copies of the contents in order to better serve users and enhance Quality of Experience (QoE). However, enabling BSs to cache data on the edge of the network brings new challenges especially on deciding on which and how the contents should be cached. Since users in the same cell may share similar content-needs, we can exploit this temporal-spatial correlation in the favor of caching system which is referred to local content popularity. Content popularity is the most important factor in the caching scheme which helps the BSs to cache appropriate data in order to serve the users more efficiently. In the edge caching scheme, the BS does not know the users request-pattern in advance. To overcome this bottleneck, a content popularity prediction using Markov Decision Process (MDP) is proposed in the second part of this thesis to let the BS know which data should be cached in each time-slot. By using the proposed scheme, core network access request can be significantly reduced and it works better than caching based on historical data in both stable and unstable content popularity

Optimal Video Streaming in Dense 5G Networks With D2D Communications

© 2017 IEEE. Mobile video traffic and mobile devices have now outpaced other data traffic and fixed devices. Global service providers are attempting to propose new mobile infrastructures and solutions for high performance of video streaming services, i.e., high quality of experience (QoE) at high resource efficiency. Although device-to-device (D2D) communications have been an emerging technique that is anticipated to provide a massive number of mobile users with advanced services in 5G networks, the management of resource and co-channel interference between D2D pairs, i.e., helper-requester pairs, and cellular users (CUs) is challenging. In this paper, we design an optimal rate allocation and description distribution for high performance video streaming, particularly, achieving high QoE at high energy efficiency while limiting co-channel interference over D2D communications in 5G networks. To this end, we allocate optimal encoding rates to different layers of a video segment and then packetize the video segment into multiple descriptions with embedded forward error correction before transmission. Simultaneously, the optimal numbers of descriptions are distributed to D2D helpers and base stations in a cooperative scheme for transmitting to the D2D requesters. The optimal results are efficiently in correspondence with intra-popularity of different segments of a video characterized by requesters' behavior, characteristic of lossy wireless channels, channel state information of D2D requesters, and constraints on remaining energy of D2D helpers and target signal to interference plus noise ratio of CUs. Simulation results demonstrate the benefits of our proposed solution in terms of high performance video streaming

Interference minimization for device-to-device (D2D) communications

In a cellular network, a central base station manages the cellular users. Direct device-to-device (D2D) communication within short-range can improve the spectral efficiency of the network. Thus D2D communication underlaying cellular networks can play a crucial role in the fifth generation (5G) network. D2D communication also enables inter-device location-based applications such as emergency social services. However, the D2D pair generates a significant amount of interference in the system while sharing resources with the cellular user. We study the allocation of the resources from the cellular users to the D2D pairs such that the total interference is minimized while guaranteeing a target sum rate. We propose a two-phase combinatorial algorithm which computes an allocation subject to the sum rate constraint. For the case when all the interference generated is uniform, the algorithm finds an optimal solution in polynomial time. We also evaluate the algorithm empirically both on synthetic and random data

Survey on the state-of-the-art in device-to-device communication: A resource allocation perspective

Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spectral efficiency of the system. Nevertheless, frequency reuse introduces significantly high interference levels thus necessitating efficient resource allocation algorithms that can enable simultaneous communication sessions through effective channel and/or power allocation. This survey paper presents a comprehensive investigation of the state-of-the-art resource allocation algorithms in D2D communication underlaying cellular networks. The surveyed algorithms are evaluated based on heterogeneous parameters which constitute the elementary features of a resource allocation algorithm in D2D paradigm. Additionally, in order to familiarize the readers with the basic design of the surveyed resource allocation algorithms, brief description of the mode of operation of each algorithm is presented. The surveyed algorithms are divided into four categories based on their technical doctrine i.e., conventional optimization based, Non-Orthogonal-MultipleAccess (NOMA) based, game theory based and machine learning based techniques. Towards the end, several open challenges are remarked as the future research directions in resource allocation for D2D communication

A game-theoretic resource allocation approach for intercell device-to-device communications in cellular networks

Device-to-Device (D2D) communication is a recently emerged disruptive technology for enhancing the performance of current cellular systems. To successfully implement D2D communications underlaying cellular networks, resource allocation to D2D links is a critical issue, which is far from trivial due to the mutual interference between D2D users and cellular users. Most of the existing resource allocation research for D2D communications has primarily focused on the intracell scenario while leaving the intercell settings not considered. In this paper, we investigate the resource allocation issue for intercell scenarios where a D2D link is located in the overlapping area of two neighboring cells. Specifically, We present three intercell D2D scenarios regarding the resource allocation problem. To address the problem, we develop a repeated game model under these scenarios. Distinct from existing works, we characterize the communication infrastructure, namely Base Stations (BSs), as players competing resource allocation quota from D2D demand, and we define the utility of each player as the payoff from both cellular and D2D communications using radio resources. We also propose a resource allocation algorithm and protocol based on the Nash equilibrium derivations. Numerical results indicate that the developed model not only significantly enhances the system performance including sum rate and sum rate gain, but also sheds lights on resource configurations for intercell D2D scenarios