In downlink multi-user multiple-input multiple-output (MU-MIMO)
systems, different users, even multiple data streams serving one user,
might require different quality-of-services (QoS). The transceiver should
allocate resources to different users aiming at satisfying their QoS
requirements. In order to design the optimal transceiver, channel
state information is necessary. In practice, channel state information
has to to be estimated, and estimation error is unavoidable. Therefore,
robust transceiver design, which takes the channel estimation
uncertainty into consideration, is important. For the previous robust
transceiver designs, bounded estimation errors or Gaussian estimation
errors were assumed. However, if there exists unknown distributed interference,
the distribution of the channel estimation error cannot be
modeled accurately a priori. Therefore, in this thesis, we investigate
the robust transceiver design problem in downlink MU-MIMO system
under probabilistic QoS constraints with arbitrary distributed channel
estimation error.
To tackle the probabilistic QoS constraints under arbitrary distributed
channel estimation error, the transceiver design problem is expressed
in terms of worst-case probabilistic constraints. Two methods are
then proposed to solve the worst-case problem. Firstly, the Chebyshev
inequality based method is proposed. After the worst-case probabilistic
constraint is approximated by the Chebyshev inequality, an
iteration between two convex subproblems is proposed to solve the
approximated problem. The convergence of the iterative method is
proved, the implementation issues and the computational complexity
are discussed.
Secondly, in order to solve the worst-case probabilistic constraint more
accurately, a novel duality method is proposed. After a series of reformulations
based on duality and S-Lemma, the worst-case statistically
constrained problem is transformed into a deterministic finite
constrained problem, with strong duality guaranteed. The resulting
problem is then solved by a convergence-guaranteed iteration between
two subproblems. Although one of the subproblems is still nonconvex,
it can be solved by a tight semidefinite relaxation (SDR).
Simulation results show that, compared to the non-robust method, the
QoS requirement is satisfied by both proposed algorithms. Furthermore,
among the two proposed methods, the duality method shows a
superior performance in transmit power, while the Chebyshev method
demonstrates a lower computational complexity. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/167228 |
| Date | January 2012 |
| Creators | He, Xin, 何鑫 |
| Contributors | Wu, YC |
| 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/B48199527 |
| 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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