Benefits of smart antennas:                                                            
Smart antenna's tasks are 1.Beamforming 2.Space time equalization  3.Diversity

1.Beamforming:

Through beamforming, smart antennas offer low co-channel interference and large antenna gain to the desired signal, leading to the better performance than conventional antenna systems. When beamforming is implemented in digital signal processing, arrays benefit from a single steerable antenna with a narrow gain pattern and no moving mechanical parts. Moreover, since beamforming is performed in software, forming several beams      with the same array is possible by simply reusing the array.
The smart antennas that use beamforming for directivity can reject co-channel interference more effectively than omni-directional antennas since the gain is lower for the direction of arrival (DOA) for the interferenve compared to the desired signal. This means that for the same transmit power, smart antennas offer increased coverage and range, higher data rate, and improved signal quality. Alternatively to achieve the same received power as a system without smart antenna, a user terminal can transmit with a reduced power, which results in lower power consumption and less interference to other users.
Smart antennas can be used to implement spatial division multiple access (SDMA). Typically, in a large cellular network (both in terms of coverage required and number of mobile users), the region is divided into a large number of cells. Some of these cells share the same frequency bands but are spaced distant enough to minimize the impact of interference. The overall band must be divided into subbands. The cells that share the same subbands are separated by the greatest distance. Because the subband is limited, capacity is limited compared to the original band. The more subbands needed to separate cell regions, the more capacity is limited.

2.Space-Time Equalizing:

Frequency selective multipath fading is a major limiting factor to data throughput in wireless communication systems. When multipath environments are encountered, frequency distortion is introduced to the received signal. For digital communication systems, this distortion results in ISI of the transmitted digital signal. Channel equalization can mitigate ISI but becomes more difficult as multipath delays increase. Alternatively, through space-time processing, an antenna array can potentially separate multipath but spatially and temporally, resulting an increased equalization performance. for CDMA systems, a technique called 2D-RAKE reception may outperform conventional RAKEs.          

3.Diversity:

A major limiting factor in the reliability of wireless communication systems is multipath fading. When only a single antenna is used and multipath is present, the amplitude of the signal component will fluctuate over time. As the fading process enters a deep fade (e.g., the amplitude of the desired signal approaches zero for a short time), reliable transmission becomes impaired. Communication systems can combat fading with FEC coding techniques. However, these techniques increase the ratio of transmit bandwidth of information data rate by a factor equql to the code rate.
Alternatively, antenna arrays can mitigate fading without a throughput penalty. Typically by simply spacing elements sufficiently far apart,fading processing on each array element will become uncorrelated. When this occurs, it becomes less likely that both will simultaneously undergo a deep fade. Hence reliability is enhanced. Many simple algorithms, such as maximum ratio combining, equal gain combining, selection diversity, and so forth, exist for achieving diversity reception.
In the next sections various processor structures suitable for narrowband field are discussed. Behavior of both element space and beamspace processors is studied when their performance is optimized. Optimization using the knowledge of the desired signal direction as well as the reference signal is considered. The processors considered include conventional beamformer; null-steering beamformer; minimum-variance distortionless beamformer, also known as optimal beamformer; generalized side-lobe canceller; and postbeamformer interference canceler. Detailed analysis of these processors in the absence of errors is carried out by deriving expressions for various performance measures. The effect of look direction errors on these processors has been analyzed to show how performance degrades because of errors.

Case Study: An Optimized Network

Consider the city Vienna covered by a UMTS network with 144 cells based on the locations of existing 2G antenna/basestation sites.

Improved Data Throughput:

A quick measure of value of smart antennas is required to see their effect on the network. A useful measure is the amount of data that can be transmitted through the network per unit time. This is expressed in kilobits per second over cell (kbit/s/cell).

At random half (50%) of the sites (72) are installed with smart antennas. In a second case these smart antennas are deployed in an optimal way. The result are shown in table 1.

Table 1 : Capacity increase of deploying 50% of smart antennas.

It follows just using smart antennas rersults in a 75% increase in network throughput.With the optimization this can be increased by a further 36%.

Improved network coverage:

Another mechanism to measure the effectiveness of optimization might be to consider thinning the network in order to reduce capital expenditure but to provide the same coverage as an "all conventional" implementation.

Smart antennas offer opportunities for considerably reducing the cost of both network roll out and operating expenditure.

Table 2 : Required cells to achieve similar coverage.

For more information about beamforming you can click 1, 2, 3, 4, 5, 6.

For more information about DOA you can click 1, 2, 3.

For more information about SDMA you can click here.

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