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This thesis presents the uniform Linear Array model of a simple adaptive antenna array based on signal-to-interference plus noise ratio (SINR) maximization.
The SINR was investigated for a conventional narrow band beam former by varying the number of antenna array elements and number of interfering signals or users. The results were compared with that of omni-directional antenna. The graph obtained showed significant improvement in SINR as the number of antenna elements increases in the presence of large interferers for odd numbered array.
Smart antennas have emerged as one of the leading innovations for achieving highly efficient networks that maximize capacity and improve quality and coverage. Smart antennas provide greater capacity and performance benefits than conventional antennas because they can be used to customize and fine-tune antenna coverage pattern to the changing traffic or radio frequency (RF) conditions in a wireless communication system like the WCDMA network.
Beam forming (BF) which is a key technology in smart antenna system is a process in which each user’s signals is multiplied by complex weight vectors that adjust the magnitude and phase of the signal from each antenna element . A beam forming appropriately combines the signals received by different elements of an antenna array to form a single output. Many
adaptive algorithms have been developed to determine the optimal weight vectors of array antenna elements dynamically, based on different performance criteria. The weight vectors produce the desired radiation pattern that can be changed dynamically, by considering the position of users and interferers to optimize the signal-to-interference and noise ratio (SINR).
1.2 Problem statement
The mobile radio propagation environment places fundamental limitations on the performance of wireless communication systems. Signals arrive at a receiver (usually the base station, BS) via a scattering mechanism and the existence of multipath with different time delays; attenuations and phases give rise to a highly complex, time-varying transmission channel. The radio channel in a wireless communication system is often characterized by multipath propagation . A fading signal results from interference between multipath components at the receiver.
The conventional antenna systems; the omni-directional antenna and the sectorized systems cannot overcome these limitations. Omni-directional antenna radiates and receives equally in all directions. This will result in wastage of power as antenna patterns are radiated in the direction of undesired users. While sectorized antenna systems multiply the use of channels which results in many handoffs between sectors , they do not overcome the major limitations of omni-directional antennas such as filtering of unwanted signals from adjacent cells. Therefore, the need for an antenna system that will minimize or overcome these limitations arises.
1.7 Objective of the work
The specific objectives of this thesis are:
1. Modeling and evaluation of a simple adaptive antenna array that can form part of a WCDMA BS structure for improving link capacity.
2. To investigate the interference and noise reduction capabilities of an adaptive antenna array.
3. Comparative analysis of omni-directional antenna and adaptive antenna array based on SINR maximization.
There is an ever – increasing demand on mobile wireless operators to provide voice and high speed data services. At the same time, these operators want to support more users per BS to reduce overall network cost and make services available to subscribers. Unfortunately, because the available broadcast spectrum is limited, attempts to increase traffic within a fixed bandwidth create more interference in the system and degrade the signal quality. To overcome this problem, adaptive antenna array is proposed for BS transceivers. This work will encourage mobile wireless operators in Nigeria to consider the option of adopting adaptive antennas at BSs due to its numerous benefits.
It will also be useful to scholars who have interest in this area of study.
1.9 Scope of the work
This work will look at adaptive filtering technique which is the principle of an adaptive antenna array. A cell model deploying adaptive antenna array at BS was proposed and a mathematical model for received signal at the antenna array derived based on uniform linear array model. The SINR of an adaptive antenna array was investigated for different antenna arrays for a conventional narrow band beam former using fixed angles of arrival considering different scenarios. Real time measurement was carried out at a test bed to obtain the signal strength and distance of mobile users from BS used in the evaluation of pathloss model described in chapter two for a typical WCDMA carrier deploying sectorized antenna at base station. The angles of arrivals (AOA) obtained from same measurement are also useful in the evaluation of SINR for adaptive
antenna. Channel model was considered as Rayleigh flat fading and antenna noise as additive white Gaussian (AWGN). The simulations are done in Matlab environment.
1.5 Thesis organization
This thesis is organized into five chapters. Chapter one deals with the introduction to the research work which includes research background, research objectives, justification and scope of the work.
In chapter two, past related works were reviewed; evolution, principles and technologies of smart antenna were explained. Channel model and the CDMA system model were illustrated. Adaptive filtering was discussed also as the basis of beam forming.
Chapter three contains methods adopted in the research. Cell model and signal model for an adaptive antenna array deployed at BS were provided. The array factor and array response vector at each element of the array were derived.
Chapter four deals with system analysis. Here, the SINR was investigated for different antenna arrays at d=0.5 and 0.75 by varying the number of array elements and the number of interfering signals for a fixed weight beam former. The comparative analysis of omni-direction antenna and adaptive antenna was done in this chapter.
Chapter 5 is Summary and conclusion. It contains summary of achievements, problems encountered and solutions, recommendations and suggestion for future research and conclusion.
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