John G. Proakis, Hanoch Lev-Ari, Zoran Zvonar
Date of Award
Doctor of Philosophy
Department or Academic Unit
College of Engineering. Department of Electrical and Computer Engineering.
broadcast channel, equalization, MIMO, precoding, spread spectrum
MIMO systems, Signal processing
Digital Communications and Networking
Proliferation of mobile data applications has increased the demand for wireless communication systems offering high throughput, wide coverage, and improved reliability. The main challenges in the design of such systems are the limited resources---such as constrained transmission power, scarce frequency bandwidth, and limited implementation complexity---and the impairments of the wireless channels, including noise, interference, and fading effects. Multiple-Input Multiple-Output (MIMO) communication has been shown to be one of the most promising emerging wireless technologies that can efficiently boost the data transmission rate, improve system coverage, and enhance link reliability. MIMO is now widely adopted by many mainstream wireless industry standards including 3GPP WCDMA/HSDPA, LTE, EVDO, WiFi, and WiMAX. By employing multiple antennas at both transmitter and receiver sides, MIMO techniques enable a new dimension---the spatial dimension---that can be utilized in different ways to combat the impairments of wireless channels. Spatial diversity provided by multiple antennas is one of the diversity techniques, which are known to be the most effective tool against fading effects of wireless channels. Spatial multiplexing exploits independent fading effects to create additional degrees of freedom, thus achieving higher capacity. Spatial diversity benefits different systems and channel types, from single user systems to multi-user systems, and from flat-fading to frequency-selective channels.
This thesis focuses on precoding and equalization techniques, for flat-fading MIMO broadcast channels, with their applications in spread spectrum communication systems. First, a novel linear precoding technique, Coordinated Interference-aware Beamforming (CIB) that utilizes channel side information at the transmitter for transmit beamforming is introduced in Chapter 2. With constrained transmitted power, CIB balances multi-user interference, spatial channel interference, and noise effects. Both analysis and the simulation results show that the achievable sum-rate of CIB bridges the rates of zero-forcing precoding and matched filtering techniques at high and low signal to noise ratios, respectively. The complexity of CIB is similar to that of other linear non-adaptive techniques; however, in addition to featuring a closed-form solution, it also allows flexible configurations on the number of antennas at the transmitter and receiver sides. In Chapter 3, we show that for the more complicated spread-spectrum systems with frequency-selective broadcast channels, the properly extended CIB can precode the signals well and inherits the some of the benefits of CIB for flat-fading channels. The role of CIB in maximizing the signal to interference plus noise ratio results in improved performance in error rates compared with other linear techniques. In Chapter 4 we introduce an innovative nonlinear eigenvalue-decomposition based lattice precoding technique (EDLP), designed for precoding and equalization for single user flat-fading channels. EDLP is a variant of dirty-paper coding and benefits from the lattice reduction, Tomlinson-Harashima precoding (THP), and linear precoding/equalization techniques. EDLP achieves full diversity and a significant power gain with an implementation complexity similar to linear techniques. In Chapter 5, we discuss linear and nonlinear precoding and equalization techniques used in flat-fading multi-user MIMO broadcast channels. We propose a BDZF-EDLP technique based on EDLP and block-diagonal zero-forcing linear precoding.
This technique offers a tradeoff among the uncoded error probability, the transmitted power, and the computational complexity at the transmitter and receiver. As a result, it achieves full receive diversity with a significantly lower complexity. It also features flexible scalability thanks to its linearly growth of its complexity. Finally, in Chapter 7, a novel finger placement strategy, Maximum Weight Placement (MWP) for the generalized RAKE (GRAKE) receivers is proposed. The MWP strategy offers a good balance between the computational complexity of the finger location placement and the resulting performance.
Summarizing, this thesis discusses linear and nonlinear techniques for precoding and equalization in different channel models that include flat-fading, frequency-selective fading, MIMO, single user, and multi-user channels. A number of novel techniques are proposed witch improve the error rate performance, throughput, and computational complexity of the communication system. These techniques include CIB for flat-fading MIMO broadcast channels, CIB-CDMA for frequency-selective fading MIMO broadcast channels, EDLP for flat-fading MIMO single-user channels and BDZF-EDLP for flat-fading MIMO broadcast channels, and MWP for spread-spectrum frequency-selective multi-user channels.
He, Jin, "Precoding and equalization for MIMO broadcast channels with applications in spread spectrum systems" (2010). Computer Engineering Dissertations. Paper 9. http://hdl.handle.net/2047/d20002063
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