Abstract

Methods for providing good spectral efficiency, without disadvantaging the delivered quality of service (QoS), in time-varying fading channels are presented. The key idea is to allocate system resources according to the encountered channel. Two approaches are examined: variable-size burst construction, and adaptive modulation. The first approach adapts the burst size according to the channel rate of change. In doing so, the available training symbols are efficiently utilized. The second adaptation approach tracks the operating channel quality, so that the most efficient modulation mode can be invoked while guaranteeing a target QoS. It is shown that these two methods can be effectively combined in a common framework for improving system efficiency, while guaranteeing good QoS. The proposed framework is especially applicable to multistate channels, in which at least one state can be considered sufficiently slowly varying. For such environments, the obtained simulation results demonstrate improved system performance and spectral efficiency.

Highlights

  • Achieving high spectral efficiency is an important goal in communication

  • It is important that the quality of service (QoS), quantified by the bit error rate (BER), will not deteriorate as a result of this goal

  • Designate the choice of available modulation modes by Vq, q = 1, . . . , Q, where Q is the total number of available modulation modes; V1 is the constellation with the least number of points; and VQ the highest

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Summary

INTRODUCTION

Achieving high spectral efficiency is an important goal in communication. it is important that the quality of service (QoS), quantified by the bit error rate (BER), will not deteriorate as a result of this goal. As will become evident in the remainder of the paper, the overall conclusion of this work is the following: if the underlying time-varying channel can be modeled as multistate, where at least one state is slowly varying, reliable communication is still possible using conventional burst-byburst techniques when coupled with a variable-size burst approach. By combining variable-size burst construction with basis-expansion modeling (BEM) of the channel [6, 7], the transmission efficiency can be improved. In this case, the system complexity is increased due to more complicated estimation and equalization procedures.

Mobile fading channels
Multistate extension
A Two-state channel example
Motivation
Accumulated received burst structure
Example construction
Comparisons to a fixed-size burst
CHANNEL EQUALIZATION AND ESTIMATION
MMSE equalization
ML channel estimation
Threshold-based change detection
Threshold function selection
Receiver processing with a variable-size burst
ADAPTIVE MODULATION
Channel metric
Threshold-based mode adaptation
Thresholds selection
Integration with variable-size burst construction
Proof of optimality
Metric errors
SIMULATION EXAMPLES
Variable-size burst in a slow-fading channel
Variable-size burst in a fast-fading channel
Variable-size burst in a two-state fading channel
Average burst length of the variable-size burst
Adaptive modulation
Adaptive modulation: throughput performance
CONCLUDING REMARKS

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