Fair Downlink Research Articles

Fair Downlink Communications for RIS-UAV Enabled Mobile Vehicles

This letter considers the sub-6GHz downlink communications from base station (BS) to mobile vehicles (MVs), where reconfigurable intelligent surface enabled unmanned aerial vehicle (RIS-UAV) serves as a mobile passive relay. To achieve communication fairness, we aim to maximize the minimum throughput among all the MVs via jointly optimizing RIS passive beamforming, MV scheduling, UAV trajectory and power allocation. The formulated problem is a mixed-integer non-convex optimization problem which is intractable to solve. Hence, the original problem is divided into three subproblems, joint passive beamforming and MV scheduling optimization, power allocation optimization, and trajectory optimization, which can be solved by the successive convex approximation (SCA) method. An alternating iterative optimization algorithm of the three subproblems is proposed to obtain the suboptimal solutions. Numerical results demonstrate the remarkable throughput gain of the proposed algorithm against other benchmarks.

Fair Downlink Transmission for Multi-Cell FD-MIMO System Exploiting Statistical CSI

In this letter, we investigate the downlink transmission for multi-cell full-dimension multiple-input multiple-output systems. Two-dimensional large-scale antenna array is deployed at each base station (BS). All cells sharing the same time-frequency resource. Based on a lower bound of the average signal to interference ratio and taking into account the fairness, we propose a downlink transmission scheme exploiting only statistical channel state information (CSI). The proposed scheme requires only a small fraction of users’ statistical CSI to be exchanged between adjacent BSs. Simulation results show that the proposed scheme can achieve good fairness, and high cell-edge and average user rate.

Fair Downlink Traffic Management for Hybrid LAA-LTE/Wi-Fi Networks

Due to the scarcity of the licensed spectrum allocated for mobile communication systems, licensed-assisted access long-term evolution (LAA-LTE) network is recently proposed to deploy in unlicensed spectrum, which is currently occupied by different Wi-Fi systems. It is a very challenging problem to ensure fair coexistence between LAA-LTE and Wi-Fi networks, in terms of spectrum sharing and traffic management. To solve this problem, a fair downlink traffic management (FDTM) scheme is proposed in this paper for hybrid LAA-LTE/Wi-Fi networks. FDTM aims to tune the minimum contention window ( $CW_{min}$ ) values and assigns feasible weights for the LAA eNBs with different traffic loads, thus to achieve; 1) fair spectrum sharing with the coexisting Wi-Fi networks in unlicensed spectrum and 2) fair service differentiation for downlink LAA-LTE traffic. Numerical results show our FDTM scheme can guarantee the throughput performance of Wi-Fi networks in shared unlicensed spectrum while supporting proportional fairness for the LAA eNBs with different traffic loads.

IVoIP: an intelligent bandwidth management scheme for VoIP in WLANs

Voice over Internet Protocol (VoIP) has been widely used by many mobile consumer devices in IEEE 802.11 wireless local area networks (WLAN) due to its low cost and convenience. However, delays of all VoIP flows dramatically increase when network capacity is approached. Additionally, unfair traffic distribution between downlink and uplink flows in WLANs impacts the perceived VoIP quality. This paper proposes an intelligent bandwidth management scheme for VoIP services (iVoIP) that improves bandwidth utilization and provides fair downlink---uplink channel access. iVoIP is a cross-layer solution which includes two components: (1) iVoIP-Admission Control, which protects the quality of existing flows and increases the utilization of wireless network resources; (2) iVoIP-Fairness scheme, which balances the channel access opportunity between access point (AP) and wireless stations. iVoIP-Admission Control limits the number of VoIP flows based on an estimation of VoIP capacity. iVoIP-Fairness implements a contention window adaptation scheme at AP which uses stereotypes and considers several major quality of service parameters to balance the network access of downlink and uplink flows, respectively. Extensive simulations and real tests have been performed, demonstrating that iVoIP has both very good VoIP capacity estimation and admission control results. Additionally, iVoIP improves the downlink/uplink fairness level in terms of throughput, delay, loss, and VoIP quality.

A Fair Downlink Scheduling Algorithm for 3GPP LTE Networks

Long Term Evolution (LTE), the standard specified by 3GPP on the way towards the fourth generation mobile networks, is intended to deliver high speed data and multimedia services to next generation mobile users. The Radio Resource Management (RRM) plays a very crucial role in managing limited radio resources to enhance system's data rate and to ensure quality of service (QoS) provisioning in both uplink and downlink. LTE downlink scheduling is a RRM entity that is responsible for the allocation of shared radio resources among mobile user equipment (UEs). One of the challenges that need to be addressed in downlink scheduling algorithms is to provide higher spectral efficiency with fairness ensured to all its users. This paper proposes a novel downlink scheduling algorithm which balances its performance between efficiency (in terms of throughput) and fairness to users. The algorithm makes use of Assignment Model for resource allocation to all the selected users during each Transmission Time Interval (TTI). The proposed algorithm is simulated and the simulation results are compared with three techniques proposed in literature. The simulator results show that the new algorithm balances well between throughput and fairness.

Bayesian link margins for opportunistic downlink packet systems

Downlink cellular packet systems utilizing opportunistic scheduling and adaptive modulation must deal with outdated channel state information. A fade margin is part of the link budget which is used to mitigate the effect of channel variation. Channel prediction reduces this margin, improving the transmission rate. We derive a fade margin which keeps packet outage constant for any prediction error variance. In our model both the signal and the interferer powers are modeled as autoregressive stochastic processes and predicted. The MMSE power predictor is also derived. Improvement in system throughput due to channel prediction is shown for a proportional fair scheduled downlink packet system, and compared to systems without prediction and opportunistic scheduling.

Rician Modeling and Prediction for Wireless Packet Data Systems

Wireless systems exploiting multi-user diversity require accurate channel state information. In this paper we examine channel prediction as a method to improve the performance of these systems. We model the outdoor channel by the Rician model, which combines diffuse spectra with a single specular component. Prediction accuracy is determined for the Rician model given various ratios (K factors) of specular to diffuse power. Simulation results show that accurate channel prediction further than one wavelength can be achieved at 30 dB SNR when the channel K factor is greater than ten. The predictor was evaluated on measured channels, and the Rician model was found to be appropriate as prediction intervals of the measured data are similar to those of synthetic data with same K factor. Using measurements some results regarding channel stationarity and optimal filter order are presented. We show for a proportionally fair scheduled downlink packet system that the predictor reduces fade margin at fixed packet outage leading to an improvement in throughput.

Efficiency-aware and fairness-aware joint-layer optimization for downlink data scheduling in OFDM

Efficiency and fairness are two crucial issues to be considered for resource allocation in multi-user wireless networks. Based on the joint optimization of physical layer and data link layer, an optimization model is derived to achieve efficient and fair downlink data scheduling in multi-user OFDM wireless networks by maximizing the total utility function with respect to the average waiting time of user queue. A dynamic sub-carrier allocation algorithm (DSAA) based on the optimization model is proposed in order to obtain the maximization of the total scheduling utility. Efficiency is improved by combining DSAA with time scale interference predictor (TSIP) which at large time scales predict ON/OFF period of user data with temporal correlation structure across multiple time scales in multi-user interference environment. Simulation results verify the efficiency and fairness of the scheme.

Utility function based fair data scheduling algorithm for OFDM wireless network

A system model is formulated as the maximization of a total utility function to achieve fair downlink data scheduling in multiuser orthogonal frequency division multiplexing (OFDM) wireless networks. A dynamic subcarrier allocation algorithm (DSAA) is proposed, to optimize the system model. The subcarrier allocation decision is made by the proposed DSAA according to the maximum value of total utility function with respect to the queue mean waiting time. Simulation results demonstrate that compared to the conventional algorithms, the proposed algorithm has better delay performance and can provide fairness under different loads by using different utility functions.