| Summary: | 博士 === 國立交通大學 === 電信工程研究所 === 99 === With the increasing demand for high-speed data rates,
multiple-input multiple-output (MIMO) antenna techniques become extremely important in current and future wireless communication systems. The huge capacity gain offered by MIMO antenna techniques can be further exploited in point-to-multiple transmissions, which can support personalized data services to multiple users concurrently. In this dissertation, we investigate MIMO antenna techniques to realize personalized parallel transmissions in
different domains.
In the first part, we utilize MIMO antenna techniques in the spatial domain to carry out personalized parallel transmissions among multiple users, named as the MIMO broadcast systems. At first, we quantitatively compare the MIMO broadcast systems with transmit and receive beamforming techniques. We find thatutilizing feedback channel state information (CSI) for user selection in the receive zero-forcing (ZF) MIMO broadcast systems is more robust to feedback channel variations compared with
utilizing feedback CSI for calculating antenna beamforming weights in the transmit MIMO broadcast systems. Next, we provide analytic formulas for the transmit MIMO broadcast systems to illustrate how multiuser scheduling can function as a link diversity compensation and soft coverage enhancement technique to improve the deficient diversity. Finally, we evaluate the effects of channel estimation
errors on the receive ZF MIMO broadcast systems. Our analysis indicates the sum rate affected by estimated channel errors will be bounded by a value as signal-to-noise ratio (SNR) increases. This result is different from the effects of feedback errors which only causes certain sum-rate degradation. In addition, channel estimation errors will also cause shrinkage on reliable coverage
and zero link diversity order on outage performance.
In the second part, an extended application of the MIMO broadcast systems, named as the network MIMO systems, transfers personalized data transmissions from single-cell scenario to multi-cell environment. In the network MIMO systems, we utilize the MIMO antenna techniques to coordinate parallel transmissions among multiple cells in geographically separated spatial domain. We propose a three-cell network MIMO architecture combined with sectorization and fractional frequency reuse (FFR) to reduce inter-cell interference in a multi-cellular system. From the
aspects of architecture and deployment, the proposed FFR-based 3-cell network MIMO architecture can not only effectively overcome the inter-cell interference, but can relieve the burden of executing complex multi-base stations joint processing for a huge number of cells.
In the third part, we apply MIMO antenna techniques to broadband orthogonal frequency division multiplexing (OFDM) system and achieve parallel transmissions among users in the frequency domain by scheduling and allocating personalized resource. Our design focuses on compensating the drawback of degraded link reliability in the diversity-deficient spatial multiplexing MIMO-OFDM systems.
First, we execute scheduling from the perspective of exploiting multiuser diversity and frequency diversity to extend the coverage region of the MIMO-OFDM systems. Our analysis and simulations indicate that the key of coverage enhancement is to jointly utilize multiuser and frequency diversity. Next, we design a scheduler to adaptively assign resource among users under a predetermined proportional rate constraint. Our method including two stages: a low-complexity subchannel allocation algorithm at first and a computational efficient power allocation method later.
Simulation results show that the proposed algorithm can achieve the capacity to the algorithm with the maximal-rate scheduling but provides better link reliability. Additionally, the proposed two-stage method can meet the predetermined rate requirements well even if service users are under different large-scale power decay conditions.
In summary, we investigate three kinds of MIMO antenna techniques to realize personalized parallel transmissions: (1) MIMO broadcast systems; (2) network MIMO systems; and (3) MIMO-OFDM systems. We utilize diversity in various domains including multiuser, frequency, and geographic location of base stations to enhance system performance in terms of link reliability, achievable reliable coverage, and sum-rate capacity.
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