690 research outputs found
A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning
In this tutorial paper, a comprehensive survey is given on several major
systematic approaches in dealing with delay-aware control problems, namely the
equivalent rate constraint approach, the Lyapunov stability drift approach and
the approximate Markov Decision Process (MDP) approach using stochastic
learning. These approaches essentially embrace most of the existing literature
regarding delay-aware resource control in wireless systems. They have their
relative pros and cons in terms of performance, complexity and implementation
issues. For each of the approaches, the problem setup, the general solution and
the design methodology are discussed. Applications of these approaches to
delay-aware resource allocation are illustrated with examples in single-hop
wireless networks. Furthermore, recent results regarding delay-aware multi-hop
routing designs in general multi-hop networks are elaborated. Finally, the
delay performance of the various approaches are compared through simulations
using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201
Resource Allocation for Outdoor-to-Indoor Multicarrier Transmission with Shared UE-side Distributed Antenna Systems
In this paper, we study the resource allocation algorithm design for downlink
multicarrier transmission with a shared user equipment (UE)-side distributed
antenna system (SUDAS) which utilizes both licensed and unlicensed frequency
bands for improving the system throughput. The joint UE selection and
transceiver processing matrix design is formulated as a non-convex optimization
problem for the maximization of the end-to-end system throughput (bits/s). In
order to obtain a tractable resource allocation algorithm, we first show that
the optimal transmitter precoding and receiver post-processing matrices jointly
diagonalize the end-to-end communication channel. Subsequently, the
optimization problem is converted to a scalar optimization problem for multiple
parallel channels, which is solved by using an asymptotically optimal iterative
algorithm. Simulation results illustrate that the proposed resource allocation
algorithm for the SUDAS achieves an excellent system performance and provides a
spatial multiplexing gain for single-antenna UEs.Comment: accepted for publication at the IEEE Vehicular Technology Conference
(VTC) Spring, Glasgow, Scotland, UK, May 201
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