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

Heterogeneous network optimization using robust power-and-resource based algorithm

In order to meet the increasing mobile data-traffic, spatial densification of network with several low-power nodes, the high-power macro BS and HetNet are the major key enabling solution. However, the HetNet is unplanned in nature, causes irregularities and interferences that without any user association rules. The appropriate deployment of the femto-cell in HetNet can provide effective traffic offloading, where the alleviate mobbing in the macro-cells can decrease the power consumption therefore it optimizes the user experience. Moreover, the protection is also important for the macro and femto cell users in a network through maintaining the min-max level of interferences. In this paper, we proposed RPRA that comprises two robust approach such as robust power-controller and the robust channel-allocation approach, which can improve the spectral efficiency and user experiences at lower network coverage areas via eliminating the week coverage zones. Also provide high user rate connection by effective interference in an efficient spectrum, lowering in transmission power and cost-effectiveness via less time delay. To show the effectiveness of our proposed model we have compared with several existing techniques and we got significant improvement in throughput, also reduction in time delay and transmission power

Secrecy Energy Efficiency in Wireless Powered Heterogeneous Networks: A Distributed ADMM Approach

OAPA This paper investigates the physical layer security in heterogeneous networks (HetNets) supported by simultaneous wireless information and power transfer (SWIPT). We first consider a two-tier HetNet composed of a macrocell and several femtocells, where the macrocell base station (BS) serves multiple users in the presence of a malicious eavesdropper, while each femtocell BS serves a couple of Internet-of-things (IoT) users. With regard to the energy constraint of IoT users, SWIPT is performed at the femtocell BSs, and IoT users accomplish the reception of information and energy in a time-switching (TS) manner, where information secrecy is to be protected. To enhance the secrecy performance, we inject artificial noise (AN) into the transmit beam at both macrocell and femtocell BSs, and for the sake of achieving green communications, we formulate the problem of maximizing secrecy energy efficiency while considering the fairness in a cross-tier multi-cell coordinated beamforming (MCBF) design. To handle this resulting nonconvex max-min fractional program problem, we propose an iterative algorithm by applying successive convex approximation method. Then, we further develop a decentralized solution based on alternative direction multiplier method (ADMM), which reduces the overhead of information exchange among coordinated BSs and achieves good approximation performance. Finally, simulation results demonstrate the performance of the proposed AN-aided cross-tier MCBF design and verify the validity of distributed ADMM-based approach

Admission control in 5G networks for the coexistence of eMBB-URLLC users

Abstract. In this thesis, we have considered the problem of admission control in 5G networks where enhanced mobile broadband (eMBB) users and ultra-reliable low-latency communication (URLLC) users coexist. Our aim is to maximize the number of admitted eMBB users to the system with a guaranteed data rate, while allocating power, bandwidth and beamforming directions to all URLLC users whose latency and reliability requirements are always guaranteed. We have considered the downlink of a multiple-input single-output (MISO) network. We have considered orthogonal spectrum sharing between these two types of users. The maximum achievable data rate by an eMBB user is modelled using the Shannon equation. As the packet length of an URLLC user is small, to model the data rate of an URLLC user, we have used the approximation of Shannon’s rate in short blocklength regime. Then, to further simplify and to obtain a lower bound for the short blocklength capacity equation, we have used the notion of effective bandwidth. This admission control problem is formulated as an l0 minimization problem. It is an NP-hard problem. We have used sequential convex programming to find a suboptimal solution to the problem. Numerically we have shown the convergence of the algorithm. With numerical results, we have shown that number of admitted users increases with the increase of the total bandwidth of the system and maximum power of the base station. Further, it decreases with the increase of the target rate for eMBB users. Moreover, we have proven with the help of numerical results that the number of admitted users is decreasing with the increase of number of URLLC users in the system

Slow admission and power control for small cell networks via distributed optimization

International audienceAlthough small cell networks are environmentally friendly and can potentially improve the coverage and capacity of cellular layers, it is imperative to control the interference in such networks before overlaying them in a macrocell network on a large-scale basis. In recent work, we developed the joint admission and power control algorithm for two-tier small cell networks in which the number of small cell users that can be admitted at their quality-of-service (QoS) constraints is maximized without violating the macrocell users' QoS constraints. The QoS metric adopted is outage probability. In this paper, we investigate the distributed implementation of the joint admission and power control problem where the small cells can determine jointly their admissibility and transmit powers autonomously