Adaptive Resource Allocation for Statistical QoS Provisioning in Mobile Wireless Communications and Networks
Date
2012-02-14
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Abstract
Due to the highly-varying wireless channels over time, frequency, and space
domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has
become a recognized feature in the next-generation wireless networks. In this dissertation,
we study the adaptive wireless resource allocation problems for statistical QoS
provisioning, such as guaranteeing the specified delay-bound violation probability,
upper-bounding the average loss-rate, optimizing the average goodput/throughput,
etc., in several typical types of mobile wireless networks.
In the first part of this dissertation, we study the statistical QoS provisioning for
mobile multicast through the adaptive resource allocations, where different multicast
receivers attempt to receive the common messages from a single base-station sender
over broadcast fading channels. Because of the heterogeneous fading across different
multicast receivers, both instantaneously and statistically, how to design the efficient
adaptive rate control and resource allocation for wireless multicast is a widely cited
open problem. We first study the time-sharing based goodput-optimization problem
for non-realtime multicast services. Then, to more comprehensively characterize the
QoS provisioning problems for mobile multicast with diverse QoS requirements, we
further integrate the statistical delay-QoS control techniques — effective capacity
theory, statistical loss-rate control, and information theory to propose a QoS-driven
optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS
requirements, sustainable traffic load, and the average loss rate through the adaptive
resource allocations and queue management. Furthermore, we study the adaptive
resource allocation problems for multi-layer video multicast to satisfy diverse statistical
delay and loss QoS requirements over different video layers. In addition,
we derive the efficient adaptive erasure-correction coding scheme for the packet-level
multicast, where the erasure-correction code is dynamically constructed based on multicast
receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile
multicast networks.
In the second part of this dissertation, we design the adaptive resource allocation
schemes for QoS provisioning in unicast based wireless networks, with emphasis
on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and
power allocation schemes for multi-user downlink transmissions (with independent
messages) in cellular networks to maximize the delay-QoS-constrained sum system
throughput. Second, we propose the delay-QoS-aware base-station selection schemes
in distributed multiple-input-multiple-output systems. Third, we study the queueaware
spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning.
Analyses and simulations are presented to show the advantages of our proposed
schemes and the impact of delay-QoS requirements on adaptive resource allocations
in various environments.
Description
Keywords
Mobile multicast, wireless networks, quality-of-service (QoS), rate adaptation, layered video coding, adaptive hybrid automatic repeat request-forward error correction (ARQ-FEC), error control, low-complexity erasure codes, statistical QoS guarantees, multiuser communications, resource allocation, effective capacity, cellular networks, optimization, power and rate control, cognitive radio networks, energy detection, spectrum sensing, wireless fading channels, multiple-input-multiple-output (MIMO), distributed MIMO