Low-Feedback Opportunistic Scheduling Schemes for Wireless Networks with Heterogenous Users

Abstract

Efficient implementation of resource sharing strategies in a multi-user wireless environment can improve the performance of a network significantly. In this thesis we study various scheduling strategies for wireless networks and handle the problem of opportunistically scheduling transmissions using channel aware schemes. First we propose a scheme that can handle users with asymmetric channel conditions and is opportunistic in the sense that it exploits the multi-user diversity of the network. The scheme requires the users to have a priori knowledge of their channel distributions. The associated overhead is limited meaning it offers reduced feedback load, that does not scale with the increasing number of users. The main technique used to shrink the feedback load is the contention based distributed implementation of a splitting algorithm that does not require explicit feedback to the scheduler from every user. The users find the best among themselves, in a distributed manner, while requiring just a ternary broadcast feedback from the scheduler at the end of each mini-slot. In addition, it can also handle fairness constraints in time and throughput to various degrees. Next we propose another opportunistic scheduler that offers most of the benefits of the previously proposed scheme but is more practical because it can also handle heterogenous users whose channel distributions are unknown. This new scheme actually reduces the complexity and is also more robust for changing traffic patterns. Finally we extend both these schemes to the scenario where there are fixed thresholds, this enables us to handle opportunistic scheduling in practical systems that can only transmit over finite number of discrete rates with the additional benefit that full feedback session, even from the selected user, is never required.

Date of Award	Jul 2012
Original language	English (US)
Awarding Institution	Computer, Electrical and Mathematical Sciences and Engineering
Supervisor	Mohamed-Slim Alouini (Supervisor)