Noor Mohammed Vali Mohamad

Device-to-Device (D2D) communication is a revolutionary technique to enhance the data rate, spectrum efficiency and energy efficiency in wireless network. It is important to have this technique due to the high demand of users and spectrum scarcity. Each D2D users can share the resource of the cellular user and transmit power of the user can create an interference to the user sharing the same resource. So, there needs a mechanism to govern the power and effectively allocate the resource to mitigate the interference created by sharing of resource between users. In this paper, D2D communication and small cells are introduced to form the Heterogeneous Network (HetNet). We propose a Sequential High Throughput Claim algorithm (SHTCA) to allocate resources to the D2D users such that Quality of Service (QoS) of the cellular users are maintained by applying the interference threshold to the cellular users. This provides the best throughput to the D2D users. Transmit power of the D2D and cellular users are optimized using the Genetic Algorithm (GA) such that interference between D2D and cellular users is effectively handled. The proposed work is differentiated over other existing algorithms and outcomes are compared in terms of energy efficiency, throughput and battery utilization in the network.

In communication technologies, device-to-device (D2D) communication is essential for resource management and power control, which are major research concerns nowadays. D2D resource allocation involves dividing vital resources, such as time, power, and spectrum, among several devices. Each device can connect to other devices via one or more frequency channels. D2D communication shares the cellular user resources, while signal power transmission causes interference to the users who share the same channel. So, there is a need to control the power of the D2D device to prevent interference. For proper power control and optimization of multi-channel D2D communication, which is a challenging task, we proposed a deep learning approach incorporating a hybrid resource allocation framework. This framework aims to increase the sum rate of D2D user equipment (DUE) while considering quality of service (QoS) factors like limiting interference to cellular user equipment (CUE) and guaranteeing individual DUE rates above a certain threshold. The proposed resource allocation scheme combines two methods, namely a metaheuristic hybrid particle swarm Cauchy approach to African vulture optimization (HPSCAV) and a modified long short-term memory (MLSTM) based approach. The HPSCAV scheme helps to ensure that the QoS constraints are met, while the MLSTM-based approach is utilized for efficient resource allocation by optimizing the power and improving it with HPSCAV. Simulation results validate that the proposed model achieved better performance in various metrics such as system capacity, power consumption, spectral efficiency (SE), and energy efficiency (EE).

Fifth generation (5G) communication network is anticipated to satisfy the need for higher data rates, less latency, ubiquitous connectivity with minimum consumption of energy and acceptable quality of Service (QoS). The massive MIMO and heterogeneous network (HetNet) has evolved as a promising technology to address the aforementioned challenges. In the proposed framework, the massive MIMO technology at the macro base station and full duplex (FD) technology enabled at the small cell base station in HetNet are investigated. An optimal antenna selection strategy, user association (UA), and power allocation (PA) in a massive MIMO‐based HetNet with FD‐enabled small cells are proposed to optimize system sum rate. Initially, the objective function of the optimization problem is nonconvex and a mixed integer nonlinear programming problem. Then, the solution is obtained by transforming the problem into convex problem utilizing Lagrangian decomposition. Simulation results manifest the effect of the number of base station antennas, number of small cell base stations, self‐interference cancellation factor, and channel state information on system sum rate. Moreover, it is evident that the propounded algorithm is effective in terms of optimizing the system sum rate when compared to the conventional maximum signal‐ to ‐ interference ‐ plus ‐noise ‐ ratio (SINR) algorithm.

Summary: Fifth generation (5G) and beyond fifth generation (B5G) networks are expected to provide more energy efficiency, spectral efficiency, and very high data rate with minimum latency to an ultradense environment. To meet the requirements of 5G and B5G standards, the network infrastructure can be network‐centric approach where the network is modified with respect to new radio signals and waveforms. The other approach is device centric where the existing network infrastructure can be efficiently utilized. Device‐to‐Device (D2D) communication is a key technique in device centric approach that supports 5G and B5G networks. We propose a Sequential Best Throughput Seek Algorithm (SBTSA), to compute the interference threshold for each Cellular User Equipment (CUE), and optimum resource blocks (RBs) are assigned to D2D pairs which provide best throughput to D2D pairs without affecting the Quality of Service (QoS) of the CUEs. The transmit power is optimized using genetic algorithm (GA) to effectively handle the interference between cellular users and D2D pairs. Proposed algorithm is compared with existing methods, and best results are obtained in terms of system throughput, battery utilization and energy efficiency.

Summary: The moment generating function (MGF)‐based approach is found as more profound as compared with probability density function (PDF)‐based counterpart for error rate analysis in any communication system. However, it fails in the case of several modulation schemes with constellation size M, such as M‐PSK, M‐QAM, and M‐PAM schemes among the others, due to the computational complexity of the involved integration. Though authors in the literature suggest alternate analytical expressions to overcome the problem it is solved only for M‐PSK and M‐QAM schemes. Hence, we present a generic MGF‐based tight approximation for the error rate analysis of different modulation schemes. Particularly, error rate analysis of M‐PAM, M‐AM, B‐PSK, B‐FSK, and orthogonal B‐FSK with non‐coherent (Non‐Co) detection modulation schemes are presented through known MGF based expressions without the evaluation of any integration. Also, a simple analytical expression for the M‐QAM modulation scheme is presented. Besides, the proposed MGF‐based analytical expressions are used to evaluate the error rate of M‐PSK, M‐PAM, and M‐AM modulation schemes over the generalized‐K (GK) fading channel, which is not presented in literature due to the computational complexity of involved integration. Newly, derived analytical expressions are validated through Monte Carlo simulation. The graphical results show the validity and accuracy of the proposed unified MGF‐based analytical expressions for error rate analysis of different modulation schemes overkμ‐gamma and GK fading channels, respectively.