Power allocation for downlink multiuser hybrid NOMA‐OMA systems: An auction game approach

Nonorthogonal multiple access (NOMA) is viewed as one of the key enabling candidate for the fifth‐generation systems. The effectiveness of such networks heavily relies on the power allocation. This paper addresses the problem of power allocation in a downlink multiuser hybrid NOMA‐orthogonal multiple access (OMA) network, where NOMA is integrated into OMA. Users with strong channel conditions are paired up with the users having weak channel conditions based on a random mechanism. Further, user pairs compete in an auction game for the transmit power being sold by the base station. Bids are placed iteratively by each user pair such that it maximizes their own utility. The existence of a unique Nash equilibrium has been proved theoretically. Simulation results show that the proposed scheme achieves higher average sum rate of users in comparison with that of the existing algorithms.     

Cross‐entropy‐based joint carrier frequency offset estimation and multiuser detection for multicarrier code division multiple access systems

This paper presents a joint carrier frequency offset estimation and multiuser detection based on a maximum likelihood approach in multicarrier code division multiple access systems. With the definition of a score function based on the log‐likelihood, the joint carrier frequency offset estimation and multiuser detection can be formulated as a nonlinear optimization problem over the joint of a multidimensional real space and a multidimensional discrete space. To reduce the computational complexity required by the joint decision statistic, while still obtaining a desirable performance, a new method using cross‐entropy optimization is proposed to solve the nonlinear optimization problem. Because of the robustness of the cross‐entropy optimization, the joint decision statistic can be efficiently solved, and, as shown by the furnished simulation results, the proposed approach can achieve satisfactory performance in various scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.     

Enhancing live virtual machine migration process via optimized resource allocation in next generation mobile edge network: A hybrid evolutionary approach

The evolution of 5th Generation wireless technology introduced Mobile Edge Computing, where edge servers are placed at the edge of the network, and are associated with evolved Node Base Stations (eNBs). This enables mobile users to offload their resource‐intensive tasks to these servers and improve network performance by reducing end‐to‐end delay. However, frequent user mobility leads to frequent re‐planning of network and increases network load. This demands dynamic Virtual Machine (VM) migration in Mobile Edge paradigm for an improved Quality of Service (QoS). For an enhanced VM migration process, an optimal pair of migrating VMs and destination edge servers needs to be chosen. In this paper, we propose an optimized decision‐making policy that chooses such optimal pairs. Several decision parameters such as average wait time, processing delay, migration delay, transmission power, and processing power are modeled. A profit function is developed using these modeled decision parameters that chooses the optimal pairs. This function is maximized using the proposed hybrid evolutionary algorithm, which combines the advantages of PSO and GA. The pairs are chosen in such a manner, that the selection guarantees high network throughput, reduced service delay, and energy consumption which is reflected in the simulation.     

Distributed fault detection for modular and reconfigurable robots with joint torque sensing: A prediction error based approach

A distributed fault detection scheme for modular and reconfigurable robots (MRRs) with joint torque sensing is proposed in this paper. With the proposed scheme, the joint torque command is filtered and compared with a filtered torque estimate derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module making it an ideal modular approach for fault detection of modular robots. Experimental results have confirmed the effectiveness of the proposed fault detection scheme.     

Expectation–maximization‐based joint data detection and channel estimation for a cellular multi‐carrier code division multiple access network using single‐hop relaying

This paper is concerned with channel estimation and data detection for a cellular multi‐carrier code division multiple access network using single‐hop relaying in the presence of frequency selective fading channels. The proposed expectation–maximization (EM) algorithm was used to jointly estimate both the coefficients of the channel between a relay and a base station and the data. EM algorithm is particularly suited to multi‐carrier code division multiple access systems because they have multi‐carrier signal format. The considered network uses single‐hop relaying technique to provide a higher quality transmission to the users with low quality channels. The base station (managing mechanism) gives them an opportunity to send their messages via the users with high quality channels in a time sharing mode. The performance of the proposed EM algorithm, with and without hopping and with cooperative communication technique, was analyzed by a computer simulation, and the results are presented. Copyright © 2011 John Wiley & Sons, Ltd.