The idea of utilizing multiple antennas (MIMO) has emerged as one of the significant breakthroughs in modern wireless communications. MIMO techniques can
improve the spectral efficiency of wireless systems and provide significant throughput
gains. As such, MIMO will be increasingly deployed in future wireless systems. On
the other hand, in order to meet the increasing demand for high data rate multimedia
wireless services, future wireless systems are evolving towards universal frequency
reuse, where neighboring cells may utilize the same radio spectrum. As such, the performance
of future wireless systems will be mainly limited by inter-cell interference
(ICI). It has been shown that the throughput gains promised by conventional MIMO
techniques degrade severely in multi-cell systems. This definitely attributes to the
existence of the ICI.
A lot of related work has been performed on the ICI mitigation or cancellation
strategies, in multi-cell MIMO systems. Most of them assume that the channel and
even data information is available at the collaborating base stations (BSs). Different
from the previous work, we are looking into certain low-complexity codebook-based
multi-cell multi-user MIMO strategies. For most of our work, we derive the statistics
of the selected user's signal-to-interference-and-noise-ratio (SINR), which enable us to
calculate the achieved sum-rate accurately and e ciently. With the derived sum-rate
expressions, we evaluate and compare the sum-rate performance for several proposed
low-complexity ICI-mitigation systems with various system parameters for single-user
per-cell scheduling case.
Furthermore, in order to fully exploit spatial multiplexing gain, we are considering
multi-user per-cell scheduling case. Based on the assumption that all CSI including
intra-cell and inter-cell channels are available at each BS, we rstly look into the centralized
optimization approach. Typically, since the sum-rate maximization problem
is mostly non-convex, it is generally di cult to obtain the globally optimum solution.
Through certain approximation and relaxations, we successfully investigate an
iterative optimization algorithm which exploits the second-order cone programming
(SOCP) approach. From the simulation results, we will observe that the iterative
option can provide near-optimum sum capacity, although only locally optimized. Afterwards,
inspired by the successful application of Per-User Unitary Rate Control
(PU2RC) scheme, we manage to extend it into dual-cell environment, with limited
coordination between two cells. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/3266 |
| Date | 29 April 2011 |
| Creators | Zhu, Jun |
| Contributors | Yang, Hong-Chuan |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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