Subband Array Implementations for Space-Time Adaptive Processing
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Subband Array Implementations for Space-Time Adaptive Processing Yimin Zhang Center for Advanced Communications, Villanova University, Villanova, PA 19085, USA Email: [email protected]
Kehu Yang Electronic Engineering Research Institute, School of Electronic Engineering, Xidian University, Xi’an, Shaanxi 710071, China Email: [email protected]
Moeness G. Amin Center for Advanced Communications, Villanova University, Villanova, PA 19085, USA Email: [email protected] Received 1 January 2004; Revised 30 June 2004 Intersymbol interference (ISI) and cochannel interference (CCI) are two primary sources of signal impairment in mobile communications. In order to suppress both ISI and CCI, space-time adaptive processing (STAP) has been shown to be effective in performing spatio-temporal equalization, leading to increased communication capacity as well as improved quality of service. The high complexity and slow convergence, however, often impede practical STAP implementations. Several subband array structures have been proposed as alternatives to STAP. These structures provide optimal or suboptimal steady-state performance with reduced implementation complexity and improved convergence performance. The purpose of this paper is to investigate the steady-state performance of subband arrays with centralized and localized feedback schemes, using different decimation rates. Analytical expressions of the minimum mean-square error (MMSE) performance are derived. The analysis assumes discrete Fourier transform (DFT)-based subband arrays and considers both unconstrained and constrained weight adaptations. Keywords and phrases: space-time adaptive processing, subband array, array processing, mobile communications, intersymbol interference, cochannel interference.
1.
INTRODUCTION
The applications of wireless communications are rapidly expanding from voice transmission to a wide class of multimedia information. With such increasing needs, wireless communication systems are developing toward higher-speed digital wireless networks. The communication channels are often frequency selective, as a result of long multipath delays relative to the symbol period, causing intersymbol interference (ISI). In many mobile communication systems, where the frequency resource is reused, cochannel interference (CCI) represents another source of channel distortion and signal impairment. Therefore, ISI and CCI are two primary sources that limit the communication capacity and the quality of services in mobile communications. While adaptive arrays are effective for spatial processing of CCI suppression; whereas adaptive equalizers are effective for temporal filtering for ISI reduction, neither of them are effective when both the CCI and ISI are present.
The use of space-time adaptive processing (STAP) technology is an effective way to perform spatio-temporal equalization that mitigates the above two problems [1, 2]. Objectives are to increase the communication capacity and enhance the quality of services. A variety of algorithms have been developed f
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