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

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 Comprehensive Review of D2D Communication in 5G and B5G Networks

The evolution of Device-to-device (D2D) communication represents a significant breakthrough within the realm of mobile technology, particularly in the context of 5G and beyond 5G (B5G) networks. This innovation streamlines the process of data transfer between devices that are in close physical proximity to each other. D2D communication capitalizes on the capabilities of nearby devices to communicate directly with one another, thereby optimizing the efficient utilization of available network resources, reducing latency, enhancing data transmission speed, and increasing the overall network capacity. In essence, it empowers more effective and rapid data sharing among neighboring devices, which is especially advantageous within the advanced landscape of mobile networks such as 5G and B5G. The development of D2D communication is largely driven by mobile operators who gather and leverage short-range communications data to propel this technology forward. This data is vital for maintaining proximity-based services and enhancing network performance. The primary objective of this research is to provide a comprehensive overview of recent progress in different aspects of D2D communication, including the discovery process, mode selection methods, interference management, power allocation, and how D2D is employed in 5G technologies. Furthermore, the study also underscores the unresolved issues and identifies the challenges associated with D2D communication, shedding light on areas that need further exploration and developmen

Resource Allocation for Device-to-Device Communications Underlaying Heterogeneous Cellular Networks Using Coalitional Games

Heterogeneous cellular networks (HCNs) with millimeter wave (mmWave) communications included are emerging as a promising candidate for the fifth generation mobile network. With highly directional antenna arrays, mmWave links are able to provide several-Gbps transmission rate. However, mmWave links are easily blocked without line of sight. On the other hand, D2D communications have been proposed to support many content based applications, and need to share resources with users in HCNs to improve spectral reuse and enhance system capacity. Consequently, an efficient resource allocation scheme for D2D pairs among both mmWave and the cellular carrier band is needed. In this paper, we first formulate the problem of the resource allocation among mmWave and the cellular band for multiple D2D pairs from the view point of game theory. Then, with the characteristics of cellular and mmWave communications considered, we propose a coalition formation game to maximize the system sum rate in statistical average sense. We also theoretically prove that our proposed game converges to a Nash-stable equilibrium and further reaches the near-optimal solution with fast convergence rate. Through extensive simulations under various system parameters, we demonstrate the superior performance of our scheme in terms of the system sum rate compared with several other practical schemes.Comment: 13 pages, 12 figure

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.Comment: 10 pages,9 figure

System to System Communication Using Mixed Mode Allocation Resource and Transmission

The mobile   communication systems with optional system-to-system (S2S) links, user components (UCs) can work in either S2S mode or mobile mode for information transport. This paper produce  mixed-mode S2S communication throughout that S2S links can work in many modes through resource multiplexing. among this framework, we tend to review the matter of increasing weighted S2S add rate beneath mobile rate constraints by optimizing mixed-mode allocation and resource allocation in term of emitted power and subchannel assignment. as a results of non-convex mobile rate constraints and binary constraints of subchannel allocation, this downside may be a non-convex mixed-integer downside that is typically hard to unravel. wetend to propose a ballroom dance approach by introducing energy-splitting variables such as mixed-mode allocation and resource allocation are decoupled and optimized severally. the following formula are distributive, desires little signal mixed and has little device  complexity. We try to gift full numerical results to demonstrate the utility of our projected formula with relevance varied network parameters

Cooperative Relaying and Resource Allocation in Future-Generation Cellular Networks

Driven by the significant consumer demand for reliable and high data rate communications, the future-generation cellular systems are expected to employ cutting-edge techniques to improve the service provisioning at substantially reduced costs. Cooperative relaying is one of the primary techniques due to its ability to improve the spectrum utilization by taking advantage of the broadcast nature of wireless signals. This dissertation studies the physical layer cooperative relaying technique and resource allocation schemes in the cooperative cellular networks to improve the spectrum and energy efficiency from the perspectives of downlink transmission, uplink transmission and device-to-device transmission, respectively. For the downlink transmission, we consider an LTE-Advanced cooperative cellular network with the deployment of Type II in-band decode-and-forward relay stations (RSs) to enhance the cell-edge throughput and to extend the coverage area. This type of relays can better exploit the broadcast nature of wireless signals while improving the utilization of existing allocated spectral resources. For such a network, we propose joint orthogonal frequency division multiplexing (OFDM) subcarrier and power allocation schemes to optimize the downlink multi-user transmission efficiency. Firstly, an optimal power dividing method between eNB and RS is proposed to maximize the achievable rate on each subcarrier. Based on this result, we show that the optimal joint resource allocation scheme for maximizing the overall throughput is to allocate each subcarrier to the user with the best channel quality and to distribute power in a water-filling manner. Since the users' Quality of Service (QoS) provision is one of the major design objectives in cellular networks, we further formulate a lexicographical optimization problem to maximize the minimum rate of all users while improving the overall throughput. A sufficient condition for optimality is derived. Due to the complexity of searching for the optimal solution, we then propose an efficient, low-complexity suboptimal joint resource allocation algorithm, which outperforms the existing suboptimal algorithms that simplify the joint design into separate allocation. Both theoretical and numerical analyses demonstrate that our proposed scheme can drastically improve the fairness as well as the overall throughput. As the physical layer uplink transmission technology for LTE-Advanced cellular network is based on single carrier frequency division multiple access (SC-FDMA) with frequency domain equalization (FDE), this dissertation further studies the uplink achievable rate and power allocation to improve the uplink spectrum efficiency in the cellular network. Different from the downlink OFDM system, signals on all subcarriers in the SC-FDMA system are transmitted sequentially rather than in parallel, thus the user's achievable rate is not simply the summation of the rates on all allocated subcarriers. Moreover, each user equipment (UE) has its own transmission power constraint instead of a total power constraint at the base station in the downlink case. Therefore, the uplink resource allocation problem in the LTE-Advanced system is more challenging. To this end, we first derive the achievable rates of the SC-FDMA system with two commonly-used FDE techniques, zero-forcing (ZF) equalization and minimum mean square error (MMSE) equalization, based on the joint superposition coding for cooperative relaying. We then propose optimal power allocation schemes among subcarriers at both UE and RS to maximize the overall throughput of the system. Theoretical analysis and numerical results are provided to demonstrate a significant gain in the system throughput by our proposed power allocation schemes. Besides the physical layer technology, the trend of improving energy efficiency in future cellular networks also motivates the network operators to continuously bring improvements in the entire network infrastructure. Such techniques include efficient base station (BS) redesign, opportunistic transmission such as device-to-device and cognitive radio communications. In the third part of this dissertation, we explore the potentials of employing cooperative relaying in a green device-to-device communication underlaying cellular network to improve the energy efficiency and spectrum utilization of the system. As the green base station is powered by sustainable energy, the design objective is to enhance both sustainability and efficiency of the device-to-device communication. Specifically, we first propose optimal power adaptation schemes to maximize the network spectrum efficiency under two practical power constraints. We then take the dynamics of the charging and discharging processes of the energy buffer at the BS into consideration to ensure the network sustainability. To this end, the energy buffer is modeled as a G/D/1 queue where the input energy has a general distribution. Power allocation schemes are proposed based on the statistics of the energy buffer to further enhance the network efficiency and sustainability. Theoretical analysis and numerical results are presented to demonstrate that our proposed power allocation schemes can improve the network throughput while maintaining the network sustainability at a certain level. Our analyses developed in this dissertation indicate that the cooperative transmission based on cooperative relaying can significantly improve the spectrum efficiency and energy efficiency of the cellular network for downlink transmission, uplink transmission and device-to-device communication. Our proposed cooperative relaying technique and resource allocation schemes can provide efficient solutions to practical design and optimization of future-generation cellular networks