Overview

This dissertation, Adaptive Packet Scheduling in OFDM Systems by Zhifeng, Diao, 刁志峰, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Adaptive Packet Scheduling in OFDM Systems Submitted by DIAO ZhiFeng for the degree of Doctor of Philosophy at The University of Hong Kong in October 2005 In this thesis, we study adaptive packet scheduling in orthogonal frequency division multiplexing (OFDM) systems. We start with a comprehensive and in-depth survey on recent research in scheduling algorithms in OFDM systems. Various representative algorithms are examined, and their advantages and disadvantages are analyzed and compared. In addition some future research directions are identified. Then we propose a new scheduler, called Channel-Condition and Packet-Length Dependent Packet Generalized Processor Sharing (CPLD-PGPS) scheduler. Based on PGPS, the CPLD scheduler considers both the physical channel condition and the length of packets, and optimally allocates the sub-carriers to different users. The total transmit power is adaptively allocated to each subchannel. With this scheduler, the system canachieve better system bit error rate (BER) performance, and correspondingly superior packet error rate (PER) performance. The system throughput is improved, the required bandwidth is guaranteed, and long term fairness for all traffic in the system is provided. In order to reduce complexity, a simplified algorithm is proposed, which maintains the system throughput as in the original scheduler, and guarantees the system performance with properly set system parameters. The superior performance of the proposed schedulers is demonstrated by simulation with multimedia traffic. For OFDM systems with smart antennas, a new packet scheduler is also introduced to maximize system throughput and guarantee the quality of service (QoS) of multimedia traffic by considering QoS requirements, packet location in the frame, and modulation level. In the frequency domain, several consecutive subchannels are grouped as a frequency subband. Each subband in a frame can transmit a packet, and can be reused by several users with smart antennas. By the BER requirements, all traffic is divided into classes. Based on this classification, we propose a dynamic packet scheduler which greatly improves system capacity and guarantees QoS requirements. Adaptive modulation is also applied in the scheduler. Our scheduler achieves higher system capacity and is far less complex than existing schedulers. The use of adaptive modulation further enhances system capacity. Simulation results demonstrate that as the traffic load increases, the new scheduler performs much better in terms of system throughput, average delay, and packet loss rate. Accurate channel information is very important in packet scheduling. We obtain such information by performing channel estimation. For OFDM systems with transmit diversity, we also analyze the performance of pilot-assisted least square (LS) and minimum mean squared error (MMSE) channel estimators. We first provide a design of orthogonal pilot sequences to simplify the estimators. When a channel tap is not sample-spaced, our analysis shows that the power of the channel tap will leak not only to other taps of the same antenna, but also to taps belonging to other antennas. We demonstrate that the MSE performance can be improved if more pilots are used, or fewer channels are estimated simultaneously. Channel estimation errors will affect the performance of different space time codes. By analysis and simulations, we find that block space time codes are a

Full Product Details

9781361059210

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available