Recently, there has been an increasing demand for OFDM system operating in
high mobility environment. In such situation, wireless channel is both
frequency-selective and time-varying, a.k.a. doubly-selective, making it hard for the
receiver to keep track of the channel state information (CSI). Moreover, the statistical
information of channel, e.g., tap positions, channel length, Doppler shifts and noise
power, is generally unknown to the receiver. In this thesis, two kinds of mobile
OFDM systems are investigated for data detection and channel estimation. Different
from previous works, which highly depend on the statistical information of the doubly
selective channel to deliver accurate channel estimation and data detection results, we
focus on more practical scenarios with unknown channel orders and Doppler
frequencies.
Firstly, point-to-point OFDM system with high mobility is considered. Due to
the unknown channel characteristics, we formulate the channel using GCE-BEM with
a large oversampling factor. The resulted GCE-BEM coefficients are sparse on
delay-Doppler domain and contain only a few nonzero elements. To enable the
identification of nonzero entries, sparsity enhancing Gaussian priors with Gamma
hyperpriors are adopted. An iterative algorithm is developed under variational
inference (VI) framework. The proposed algorithm iteratively estimate the channel,
recover the unknown data using Viterbi algorithm and learn the channel and noise
statistical information, using only limited number of pilot subcarrier in one OFDM
symbol.
Secondly, we investigate multihop amplify-and-forward (AF) OFDM system,
where system structure is generally unknown to the receiver due to the variable
number of hops and relaying paths in high mobility environment. We notice that in AF
relaying systems, the composite source-relay-destination channel is sufficient for data
detection. Then we integrate the multilink, multihop channel matrices into one
composite channel matrix, which turns out to have the same structure as the
point-to-point OFDM channel. The reformulated system model is more concise and a
similar iterative algorithm to that of the point-to-point case can be derived to estimate
the composite channel and detect data. This means that the proposed framework
applies to OFDM system under high mobility regardless of the system structure.
Simulation results show that the performance of the proposed algorithm is very
close to that of the optimal channel estimation and data detection algorithm, which
requires specific information of system structure, channel tap positions, channel
lengths, Doppler shifts as well as noise powers. It is worth noting that, the
close-to-ideal performance of the proposed algorithms is achieved with none of the
above information. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/174383 |
| Date | January 2011 |
| Creators | Min, Rui, 闵瑞 |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B47323930 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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