Max-Min Fair RIS-Aided Rate-Splitting Multiple Access for Multigroup Multicast Communications

Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reconfigurable intelligent surface(RIS)technique can be introduced to assist wireless communications through enhancing the channel quality.In RIS-aided RSMA multigroup multicasting,how to provide fair and high-quality multiuser service under power and spectrum constraints is essential.In this paper,we propose a max-min fair RIS-aided rate-splitting multiple access(MMF-RISRSMA)scheme for multigroup multicast communications,where the rate fairness is obtained by maximizing the minimum group-rate.In doing so,we jointly optimize the beamformers,the rate splitting vector at the transmitter,as well as the phase shifts at RIS.To solve it,we divide the original optimization problem into two subproblems and alternately optimize the variables.The beamforming and rate splitting optimization subproblem is solved by using the successive convex approximation technique.The phase shift optimization subproblem is solved through the penalty function method to achieve a rank-one locally optimal solution.Simulations demonstrate that the proposed MMF-RIS-RSMA scheme can obtain significant performance gain in terms of the minimum group-rate.

DMMF: Dominant and Max-Min Fair Allocation in Satellite Networks

Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consists of two allocation stages, dominant resource fair(DRF) allocation stage and max-min fairness(MMF) allocation stage. The proposed DMMF scheme exhibits desirable properties, including share incentive, strategy proofness, envy freeness and Pareto optimality. Meanwhile, DMMF can improve the allocation efficiency and reach 100% allocation efficiency.

Mobile-Service Based Max-Min Fairness Resource Scheduling for Heterogeneous Vehicular Networks

This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside infrastructure and other moving vehicles. For such a system, we propose a mobile-service based max-min fairness resource scheduling scheme, where service amount which is more suitable for high mobility scenarios is adopted to characterize the information transmission capacity of the links and the max-min criteria is adopted to meet the fairness requirement of the moving vehicles. Simulation results demonstrate the effectiveness of our proposed scheme. It is shown that our proposed scheme archives higher throughput and better fairness compared with random scheduling scheme and non-relaying scheme.

Fairness-Oriented Hybrid Precoding for Massive MIMO Maritime Downlink Systems with Large-Scale CSIT

Different from conventional cellular networks, a maritime communication base station(BS) has to cover a much wider area due to the limitation of available BS sites. Accordingly the performance of users far away from the BS is poor in general. This renders the fairness among users a challenging issue for maritime communications. In this paper, we consider a practical massive MIMO maritime BS with hybrid digital and analog precoding. Only the large-scale channel state information at the transmitter(CSIT) is considered so as to reduce the implementation complexity and overhead of the system. On this basis, we address the problem of fairness-oriented precoding design. A max-min optimization problem is formulated and solved in an iterative way. Simulation results demonstrate that the proposed scheme performs much better than conventional hybrid precoding algorithms in terms of minimum achievable rate of all the users, for the typical three-ray maritime channel model.

RIS-Aided Constant-Envelope Beamforming for Multiuser Wireless Power Transfer:A Max-Min Approach

As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we consider a multiuser multiple-input single-output(MISO)wireless power transfer(WPT)system,which is assisted by several RISs.In order to improve energy efficiency and reduce hardware cost,we consider that the energy transmitter(ET)in the WPT system is equipped with a constant-envelope analog beamformer,instead of a digital beamformer.Focusing on user fairness,we study a minimum received power maximization problem by jointly optimizing the ET beamforming and the RIS phase shifts,subject to the constant-envelope constraints.We iteratively solve this non-convex maxmin problem by leveraging both the successive convex approximation(SCA)method and the alternating direction method of multipliers(ADMM)algorithm.Numerical results demonstrate the effectiveness of the proposed algorithm and show attractive performance gain brought by RISs.

A NEW ABR CONGESTION CONTROL ALGORITHM ACHIEVING FAIRNESS UNDER SEVERAL CRITERIA

All ABR congestion control algorithms reported are designed to achieve max-min fairness. In this paper, a new algorithm named dynamic bandwidth allocation algorithm is presented. Under the same framework, the algorithm can achieve fairness under several given criteria. Simulation result shows that the new algorithm works well under various network configurations, various traffic classes, and scale well to LANs or WANs.

Energy efficient resource allocation for D2D multicast communications

The resource allocation for device-to-device(D2D)multicast communications is investigated.To achieve fair energy efficiency(EE)among different multicast groups,the max-min fairness criterion is used as the optimization criterion and the EE of D2D multicast groups are taken as the optimization objective function.The aim is to maximize the minimum EE for different D2D multicast groups under the constraints of the maximum transmit power and minimum transmit rate,which is modeled as a non-convex and mixed-integer fractional programming problem.Here,suboptimal resource allocation algorithms are proposed to solve this problem.First,channel assignment scheme is performed to assign channel to D2D multicast groups.Second,for a given channel assignment,iterative power allocation schemes with and without loss of cellular users’rate are completed,respectively.Simulation results corroborate the convergence performance of the proposed algorithms.In addition,compared with the traditional throughput maximization algorithm,the proposed algorithms can improve the energy efficiency of the system and the fairness achieved among different multicast groups.

Optimal power allocation for downlink two-user non-orthogonal multiple access in visible light communication

In this work,we consider employing the NOMA(Non-Orthogonal Multiple Access)technique in downlink VLC(Visible Light Communication)for performance enhancement.In particular,focusing on a typical NOMA scenario with two users,we optimize the power allocation strategies under both sum-rate maximization and max-min fairness criteria,where practical optical power and QoS(Quality of Service)constraints are included.As our main contribution,we achieve optimal power allocation solutions in semi-closed forms via mathematical analysis,which,to the best of our knowledge,have not been reported in literature.Simulation results demonstrate that NOMA can provide remarkable performance gains over OMA(Orthogonal Multiple Access)in the context of VLC downlinks.