Selective Fair Scheduling over Fading Channels

Imposing fairness in resource allocation incurs a loss of system throughput, known as the Price of Fairness ($PoF$). In wireless scheduling, $PoF$ increases when serving users with very poor channel quality because the scheduler wastes resources trying to be fair. This paper proposes a novel resource allocation framework to rigorously address this issue. We introduce selective fairness: being fair only to selected users, and improving $PoF$ by momentarily blocking the rest. We study the associated admission control problem of finding the user selection that minimizes $PoF$ subject to selective fairness, and show that this combinatorial problem can be solved efficiently if the feasibility set satisfies a condition; in our model it suffices that the wireless channels are stochastically dominated. Exploiting selective fairness, we design a stochastic framework where we minimize $PoF$ subject to an SLA, which ensures that an ergodic subscriber is served frequently enough. In this context, we propose an online policy that combines the drift-plus-penalty technique with Gradient-Based Scheduling experts, and we prove it achieves the optimal $PoF$. Simulations show that our intelligent blocking outperforms by 40$\%$ in throughput previous approaches which satisfy the SLA by blocking low-SNR users

On Queue-Aware Power Control in Interfering Wireless Links: Heavy Traffic Asymptotic Modelling and Application in QoS Provisioning

International audienceIn this work we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We deal with this problem using heavy traffic approximation techniques which lead to an asymptotic model of a (controlled) stochas-tic differential equation. The proposed power control strategy consists of allocating most of the power according to the states of the channel and a smaller fraction according to the queue lengths, for which we find a closed-form expression. We first consider a scenario where all channel realizations and queue lengths are known instantaneously to every transmitter. Then, the algorithm is extended to the case where only local SINR feedback is available and when queue length information is shared with delays among the transmitters. These models and results are also extended to the case where the transmitters are equipped with multiple antennas. Finally, the applicability in practical system settings are discussed and simulation results are provided to illustrate the performance of the proposed method

A Heavy Traffic Approach for Queue-Aware Power Control in Interfering Wireless Links

978-1-4673-0970-7International audienceIn this work, we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We address this problem using heavy traffic approximation techniques which lead to an asymptotic model described by a (controlled) stochastic differential equation. The power control strategy consists in allocating most of the power according to the wireless channel state and a smaller fraction according to the queue lengths. Simulation results in a simple setting illustrate that the proposed control policy can yield desirable results in practical systems

Heavy Traffic Asymptotic Approach for Video Streaming over Small Cell Networks with Imperfect State Information

International audienceIn this work, we address the problem of decentralized power allocation for satisfying individual QoS constraints in video streaming in a Small Cells Network.They QoS metric we use here is the probability that the queue length at each transmitter exceeds some threshold: we want this probability to be fixed at a desired value. We focus on a model with interfering transmitter-receiver pairs. Using heavy traffic asymptotic modelling we propose a power control algorithm for the case where each base station has access to local SINR feedback, information about the queue length of its user and delayed information of the queues in the other base stations. Simulation results suggest that the proposed algorithm is quite robust in the case of delayed information sharing