The textbook definition of a smart antenna is “an antenna array with digital signal processing algorithms, which identify spatial signatures.” Using these spatial signatures, the smart antenna calculates beamforming vectors, which are then used to track and locate the antenna beam on a mobile or target.
Just as the phrase implies, signal processing algorithms are sequences of computer-implementable instructions for analyzing, modifying, and synthesizing signals (in this case, radiofrequency signals). A spatial signal signature is a response vector of an antenna to a mobile unit at a certain location. An example of a signal signature would be a signal’s direction of arrival (DOA). Calculating a DOA involves finding a spatial spectrum of antenna array and defining its peaks. Because the computations are very intensive, the smart antenna’s signal processing algorithms prove to be very useful.
Some of the most common smart antenna applications include acoustic signal processing, track and scan radar, and cellular systems such as 5G and LTE. The main difference between reconfigurable antennas and smart antennas is that reconfigurable antennas are single-element antennas instead of antenna arrays.
The two main types of smart antennas are switched-beam smart antennas and and adaptive arrays.
Switched-beam systems can choose from one of many predefined patterns in order to enhance the received signal. The overall goal of the switched-beam system is to increase the gain according to the location of the user.
In a previous post, we briefly explained that adaptive beamformers adjust to differing situations in order to maximize or minimize signal-to-interference-plus-noise ratio (SINR), which helps measure the quality of wireless communication.
Smart antennas provide many benefits.
The main benefit of smart antenna systems is its ability to simultaneously increase the useful receiving signal and lower the interference level, increasing the signal-to-interference ratio (SIR) in more densely populated areas. Smart antennas can essentially filter out the unwanted noise made by other users in the system so that important signals can be transmitted and received clearly.
Additionally, because smart antennas are more directional than omnidirectional and sectorized antennas, they can focus their energy toward the intended users, instead of wasting it by directing it in unnecessary directions. This means that base stations can be spaced further apart, as they would be in less-populated areas.
Smart antennas are also harder to tap into. In order to successfully tap into the connection, the intruder must be positioned in the same direction as their user as seen from the base station. Consequently, smart antennas provide more security, making them extremely vital in the present day, where organizations and individuals routinely transmit confidential information to one another.
Lastly, smart antennas’ spatial detection capabilities allow for geo-location services. For example, they can locate humans in emergency situations.
Smart antennas also have their limitations.
Smart antenna transceivers are much more complex than those of traditional base station transceivers in that smart antennas need separate transceiver chains for each array antenna element. This also means that that each transceiver needs to be accurately calibrated at all times. Additionally, smart antenna base stations must be equipped with very powerful digital signal processors to handle the computationally-intensive beamforming. This translates to higher costs in the short-term, however, the benefits will outweigh the costs over time.
The term beamforming refers to a method of directing a wireless signal towards a specific receiving device, whereas the alternative would be allowing the signal to spread in all directions from a transmitter the way it naturally would.
By focusing a signal in a specific direction, beamforming delivers higher signal quality to a receiver. This means information is transmitted faster and more accurately. Furthermore, this accuracy can be reached without boosting broadcast power.
Example of Radiation Pattern with
a Fixed Beamformer
Example of Radiation Pattern with
an Adaptive Beamformer
An antenna array is comprised of multiple radiating elements, each of which contributes an element pattern to the array’s radiation pattern. Each element pattern is a spatial distribution of RF power arising from the amplitude and phase of the RF signal at the element’s RF feed point. The array’s radiation pattern is determined by the coherent sum of all element fields, each which may be “weighted” by an additional amplitude and phase. Such weighted patterns exemplify beamforming in the array, whereby sidelobe levels and nulls are produced and controlled by adjusting the element weights.
Beamforming techniques loosely fall into two categories: conventional and adaptive.
Fixed beamforming generally describes a conventional technique where the antenna array pattern is obtained from fixed element weights that do not depend on the signal environment. Conversely, adaptive beamforming element weights that do depend on —and can adapt to— the signal environment via some feedback mechanism.
Adaptive beamforming, which was initially developed in the 1960s, uses a digital signal processor (DSP) to compute the complex weights using an adaptive algorithm, which then generates an array factor for an optimal signal-to-interference-plus-noise ratio (SINR). Basically, adaptive beamformers are designed to adjust to differing situations in order to maximize or minimize SINR, which helps measure the quality of wireless communication.
The average civilian experiences adaptive beamforming technology in their every day life. In fact, wireless carriers use adaptive beamforming to provide next-generation wireless communications (5G) and long-term evolution (LTE) services.