Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-latency

In this paper, we study the coexistence and synergy between edge and central cloud computing in a heterogeneous cellular network (HetNet), which contains a multi-antenna macro base station (MBS), multiple multi-antenna small base stations (SBSs) and multiple single-antenna user equipment (UEs). The SBSs are empowered by edge clouds offering limited computing services for UEs, whereas the MBS provides high-performance central cloud computing services to UEs via a restricted multiple-input multiple-output (MIMO) backhaul to their associated SBSs. With processing latency constraints at the central and edge networks, we aim to minimize the system energy consumption used for task offloading and computation. The problem is formulated by jointly optimizing the cloud selection, the UEs' transmit powers, the SBSs' receive beamformers, and the SBSs' transmit covariance matrices, which is {a mixed-integer and non-convex optimization problem}. Based on methods such as decomposition approach and successive pseudoconvex approach, a tractable solution is proposed via an iterative algorithm. The simulation results show that our proposed solution can achieve great performance gain over conventional schemes using edge or central cloud alone. Also, with large-scale antennas at the MBS, the massive MIMO backhaul can significantly reduce the complexity of the proposed algorithm and obtain even better performance.Comment: Accepted in IEEE Transactions on Wireless Communication

MM-Wave HetNet in 5G and beyond Cellular Networks Reinforcement Learning Method to improve QoS and Exploiting Path Loss Model

This paper presents High density heterogeneous networks (HetNet) which are the most promising technology for the fifth generation (5G) cellular network. Since 5G will be available for a long time, previous generation networking systems will need customization and updates. We examine the merits and drawbacks of legacy and Q-Learning (QL)-based adaptive resource allocation systems. Furthermore, various comparisons between methods and schemes are made for the purpose of evaluating the solutions for future generation. Microwave macro cells are used to enable extra high capacity such as Long-Term Evolution (LTE), eNodeB (eNB), and Multimedia Communications Wireless technology (MC), in which they are most likely to be deployed. This paper also presents four scenarios for 5G mm-Wave implementation, including proposed system architectures. The WL algorithm allocates optimal power to the small cell base station (SBS) to satisfy the minimum necessary capacity of macro cell user equipment (MUEs) and small cell user equipment (SCUEs) in order to provide quality of service (QoS) (SUEs). The challenges with dense HetNet and the massive backhaul traffic they generate are discussed in this study. Finally, a core HetNet design based on clusters is aimed at reducing backhaul traffic. According to our findings, MM-wave HetNet and MEC can be useful in a wide range of applications, including ultra-high data rate and low latency communications in 5G and beyond. We also used the channel model simulator to examine the directional power delay profile with received signal power, path loss, and path loss exponent (PLE) for both LOS and NLOS using uniform linear array (ULA) 2X2 and 64x16 antenna configurations at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS (NYUSIM). The simulation results show the performance of several path loss models in the mmWave and sub-6 GHz bands. The path loss in the close-in (CI) model at mmWave bands is higher than that of open space and two ray path loss models because it considers all shadowing and reflection effects between transmitter and receiver. We also compared the suggested method to existing models like Amiri, Su, Alsobhi, Iqbal, and greedy (non adaptive), and found that it not only enhanced MUE and SUE minimum capacities and reduced BT complexity, but it also established a new minimum QoS threshold. We also talked about 6G researches in the future. When compared to utilizing the dual slope route loss model alone in a hybrid heterogeneous network, our simulation findings show that decoupling is more visible when employing the dual slope path loss model, which enhances system performance in terms of coverage and data rate

Resource allocation in non-orthogonal multiple access technologies for 5G networks and beyond.

Doctoral Degree. University of KwaZulu-Natal, Durban.The increasing demand of mobile and device connectivity poses challenging requirements for 5G wireless communications, such as high energy- and spectral-efficiency and low latency. This necessitates a shift from orthogonal multiple access (OMA) to Non-Orthogonal Multiple Access (NOMA) techniques, namely, power-domain NOMA (PD-NOMA) and code-domain NOMA (CD-NOMA). The basic idea behind NOMA schemes is to co-multiplex different users on the same resource elements (time slot, OFDMA sub-carrier, or spreading code) via power domain (PD) or code domain (CD) at the transmitter while permitting controllable interference, and their successful multi-user detection (MUD) at the receiver albeit, increased computational complexity. In this work, an analysis on the performance of the existing NOMA schemes is carried out. Furthermore, we investigate the feasibility of a proposed uplink hybrid-NOMA scheme namely power domain sparse code multiple access (PD-SCMA) that integrates PD-NOMA and CD-NOMA based sparse code multiple access (SCMA) on heterogeneous networks (HetNets). Such hybrid schemes come with resource allocation (RA) challenges namely; codebook allocation, user pairing and power allocation. Therefore, hybrid RA schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic macro cell user equipment (MUE)- small cell user equipment (SUE) pairing (OMSP) for user pairing (UP), and a QoS-aware power allocation (QAPA) for power allocation (PA) are developed for an energy efficient (EE) system. The performance of the RA schemes is analyzed alongside an analytical RA optimization algorithm. Through numerical results, the proposed schemes show significant improvements in the EE of the small cells in comparison with the prevalent schemes. Additionally, there is significant sum rate performance improvement over the conventional SCMA and PD-NOMA. Secondly, we investigate the multiplexing capacity of the hybrid PD-SCMA scheme in HetNets. Particularly, we investigate and derive closed-form solutions for codebook capacity, MUE multiplexing and power capacity bounds. The system’s performance results into low outage when the system’s point of operation is within the multiplexing bounds. To alleviate the RA challenges of such a system at the transmitter, dual parameter ranking (DPR) and alternate search method (ASM) based RA schemes are proposed. The results show significant capacity gain with DPR-RA in comparison with conventional RA schemes. Lastly, we investigate the feasibility of integrating the hybrid PD-SCMA with multiple-input multipleoutput (MIMO) technique namely, M-PD-SCMA. The attention to M-PD-SCMA resides in the need of lower number of antennas while preserving the system capacity thanks to the overload in PDSCMA. To enhance spectral efficiency and error performance we propose spatial multiplexing at the transmitter and a low complex joint MUD scheme based on successive interference cancellation (SIC) and expectation propagation algorithm (EPA) at the receiver are proposed. Numerical results exhibit performance benchmark with PD-SCMA schemes and the proposed receiver achieves guaranteed bit error rate (BER) performance with a bounded increase in the number of transmit and receive antennas. Thus, the feasibility of an M-PD-SCMA system is validated