Spatio-Temporal processing for Optimum Uplink-Downlink WCDMA Systems

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAl). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this research we investigate computationally simpler technique termed as a Beamfom1er-Rake. In a Beamformer-Rake, the output of a beamfom1er is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) and beyond (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband COMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. We consider three different Pilot Symbol Assisted (PSA) beamforming techniques, Direct Matrix Inversion (DMI), Least-Mean Square (LMS) and Recursive Least Square (RLS) adaptive algorithms. Geometrically Based Single Bounce (GBSB) statistical Circular channel model is considered, which is more suitable for array processing, and conductive to RAKE combining. The performances of the Beam former-Rake receiver are evaluated in this channel model as a function of the number of antenna elements and RAKE fingers, in which are evaluated for the uplink WCDMA system. It is shown that, the Beamformer-Rake receiver outperforms the conventional RAKE receiver and the conventional beamformer by a significant margin. Also, we optimize and develop a mathematical formulation for the output Signal to Interference plus Noise Ratio (SINR) of a Beam former-Rake receiver. In this research, also, we develop, simulate and evaluate the SINR and Signal to Noise Ratio (Et!Nol performances of an adaptive beamforming technique in the WCDMA system for downlink. The performance is then compared with an omnidirectional antenna system. Simulation shows that the best perfom1ance can be achieved when all the mobiles with same Angle-of-Arrival (AOA) and different distance from base station are formed in one beam

A combined channel-modified adaptive array MMSE canceller and viterbi equalizer

In this thesis, a very simple scheme is proposed which couples a maximum-likelihood sequence estimator (MLSE) with a X-element canceller. The method makes use of the MLSE\u27s channel estimator to modify the locally generated training sequence used to calculate the antenna array weights. This method will increase the array\u27s degree of freedom for interference cancellation by allowing the dispersive, desired signal to pass through the array undisturbed. Temporal equalization of the desired signal is then accomplished using maximum-likelihood sequence estimation. The T-spaced channel estimator coefficients and the array weights are obtained simultaneously using the minimum mean square error criteria. The result is a X-element receiver structure capable of canceling X- 1 in-band interferences without compromising temporal equalization

Successive DF relaying: MS-DIS aided interference suppression and three-stage concatenated architecture design

Conventional single-relay aided two-phase cooperative networks employing coherent detection algorithms incur a significant 50% throughput loss. Furthermore, it is unrealistic to expect that in addition to the task of relaying, the relay-station would dedicate further precious resources to the estimation of the source-relay channel in support of coherent detection. In order to circumvent these problems, we propose decode and-forward (DF) based successive relaying employing noncoherent detection schemes. A crucial challenge in this context is that of suppressing the successive relaying induced interference, despite dispensing with any channel state information (CSI). We overcome this challenge by introducing a novel adaptive Newton algorithm based multiple-symbol differential interference suppression (MS-DIS) scheme. Correspondingly, a three-stage concatenated transceiver architecture is devised. We demonstrate that our proposed system is capable of near-error-free transmissions at low signal-to-noise ratios

Spatio-Temporal processing for Optimum Uplink-Downlink WCDMA Systems

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAl). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this research we investigate computationally simpler technique termed as a Beamfom1er-Rake. In a Beamformer-Rake, the output of a beamfom1er is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) and beyond (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband COMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. We consider three different Pilot Symbol Assisted (PSA) beamforming techniques, Direct Matrix Inversion (DMI), Least-Mean Square (LMS) and Recursive Least Square (RLS) adaptive algorithms. Geometrically Based Single Bounce (GBSB) statistical Circular channel model is considered, which is more suitable for array processing, and conductive to RAKE combining. The performances of the Beam former-Rake receiver are evaluated in this channel model as a function of the number of antenna elements and RAKE fingers, in which are evaluated for the uplink WCDMA system. It is shown that, the Beamformer-Rake receiver outperforms the conventional RAKE receiver and the conventional beamformer by a significant margin. Also, we optimize and develop a mathematical formulation for the output Signal to Interference plus Noise Ratio (SINR) of a Beam former-Rake receiver. In this research, also, we develop, simulate and evaluate the SINR and Signal to Noise Ratio (Et!Nol performances of an adaptive beamforming technique in the WCDMA system for downlink. The performance is then compared with an omnidirectional antenna system. Simulation shows that the best perfom1ance can be achieved when all the mobiles with same Angle-of-Arrival (AOA) and different distance from base station are formed in one beam

Knowledge-Aided STAP Using Low Rank and Geometry Properties

This paper presents knowledge-aided space-time adaptive processing (KA-STAP) algorithms that exploit the low-rank dominant clutter and the array geometry properties (LRGP) for airborne radar applications. The core idea is to exploit the fact that the clutter subspace is only determined by the space-time steering vectors, {red}{where the Gram-Schmidt orthogonalization approach is employed to compute the clutter subspace. Specifically, for a side-looking uniformly spaced linear array, the} algorithm firstly selects a group of linearly independent space-time steering vectors using LRGP that can represent the clutter subspace. By performing the Gram-Schmidt orthogonalization procedure, the orthogonal bases of the clutter subspace are obtained, followed by two approaches to compute the STAP filter weights. To overcome the performance degradation caused by the non-ideal effects, a KA-STAP algorithm that combines the covariance matrix taper (CMT) is proposed. For practical applications, a reduced-dimension version of the proposed KA-STAP algorithm is also developed. The simulation results illustrate the effectiveness of our proposed algorithms, and show that the proposed algorithms converge rapidly and provide a SINR improvement over existing methods when using a very small number of snapshots.Comment: 16 figures, 12 pages. IEEE Transactions on Aerospace and Electronic Systems, 201

An efficient reconfigurable optimal source detection and beam allocation algorithm for signal subspace factorization

Now a days, huge amount of data is communicated through channels in wireless network. It requires an efficient parallel operation for the optimal utilization of frequency, time allocation and coding model for signal subspace factorization in smart antenna. In view of this requirement, an efficient reconfigurable optimal source detection and beam allocation algorithm (RoSDBA) is proposed. The proposed algorithm is able to allocate desired signal to the user space to reduce the noise and also for efficient allocation of subspace to remove disturbance in all directions. The proposed method efficiently utilizes the antenna array elements by accurate identification and allocation of antenna array elements such as individual radiators, radiation beam, signal strength, and disturbance factor. With respect to simulation analysis, the proposed method shows better performance for the resolution, radiation beam allocations, identification bias, distribution factor and time taken for the detection of various array arrangements and source numbers

Adaptive space-time processing for wireless communications

Adaptive space-time processing techniques have been found to increase the capacity of two major, multiple-access wireless communication systems: Time Division Multiple Access (TDMA) and Code Division Multiple Access (CDMA). In an IS-54 TDMA system, the frequency re-use factor has to be set to 7 so that cells with the same spectrum are separated far enough to meet a required carrier-to-interference ratio (CIR). Space processing uses multiple antennas which, in turn, provide alternative signal paths in order to cancel interferences and combat multipath fading. We have proposed the eigencanceler method and have reviewed the theoretical optimum combining and the feasible direct matrix inverse (DMI) technique. An analysis of the system performance reveals that when data sets are small, the eigencanceler is superior to DMI. Furthermore, we have proposed a. simple projection-based algorithm and have analyzed its performance. The capacity of CDMA communication systems is restricted by multiple-access interferences (MAI). We have shown that spatial and temporal processing can be combined to increase the capacity of CDMA-based wireless communications systems. The degrees of freedom provided by space-time processing can be exploited to combat both fading and MAI. Specifically, we have discussed the following methods: (1) space-time diversity, (2) cascade optimum spatial-diversity temporal, (3) cascade optimum spatial-optimum temporal, and (4) joint-domain optimum processing. We have proved that, due to its interference cancellation capability, optimum combining provides significantly better performance than diversity techniques

New detection schemes for DS/CDMA with antenna arrays.

by Siu-Lung Hui, Freeman.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 64-[67]).Abstract also in Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Use of Antenna Arrays in Mobile Communications --- p.1Chapter 1.1.1 --- Overview --- p.1Chapter 1.1.2 --- Beamforming --- p.2Chapter 1.2 --- DS/CDMA System s and Multiple Access Interferences --- p.4Chapter 1.3 --- Multiuser Detection Schemes --- p.7Chapter 1.4 --- Outline of Thesis --- p.11Chapter 2 --- A Blind Adaptive Receiver with Antenna Arrays and M-ary Orthogonal Data Signals --- p.13Chapter 2.1 --- Introduction --- p.13Chapter 2.2 --- System Model --- p.15Chapter 2.3 --- Eigen-Analysis Algorithm --- p.21Chapter 2.4 --- Simulation Results --- p.92Chapter 2.5 --- Adaptive Algorithm --- p.27Chapter 2.6 --- Summary --- p.30Chapter 3 --- Detection with the Use of the Two-Stage Spreading Scheme --- p.32Chapter 3.1 --- Introduction --- p.32Chapter 3.2 --- System Model --- p.34Chapter 3.3 --- Blind Beamforming --- p.36Chapter 3.4 --- Blind Adaptive Multiuser Detection without Antenna Arrays --- p.38Chapter 3.4.1 --- Stochastic Gradient Descent Algorithm --- p.40Chapter 3.4.2 --- Alternative Matrix Approach --- p.41Chapter 3.5 --- Theoretical Combined Receiver Model --- p.41Chapter 3.6 --- Practical Implementation of the Receiver --- p.50Chapter 3.6.1 --- Combined Scheme with Adaptive Algorithms --- p.50Chapter 3.6.2 --- Simplified Structure --- p.52Chapter 3.7 --- Summary --- p.54Chapter 4 --- Conclusions and Future Work --- p.55Chapter A --- Correlation Properties --- p.58Chapter B --- Adaptive Algorithm --- p.62Bibliography --- p.6