Beam steering, which permits strong directed beams towards the receiver to combat excessive pathloss, especially for higher frequency bands, immediately comes to mind when discussing mathematical aspects of Beamforming in MIMO antennas. On the other side, it also lessens signal interference and improves the effectiveness of spatial multiplexing in Massive MIMO communication. Let's go right to the mathematical parts of Beamforming, which will make it easier for you to code in Python and MATLAB.
1. Beam Steering (Analog Beamforming)
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In the first stage, the BS applies beam steering at the side of the mobile station (MS) while the MS enables omnidirectional transmission. In the following step, the MS uses beam steering while the BS is an omnidirectional transmitter. The best beamformer and combiner pair are then identified at BS & MS, and they make communication available. Following is an outline of the codebook: .png)
Let's say a small town or village has a cell tower in the midst of it. Now everybody can understand the cell tower's 360-degree coverage area (if not, you restrict the coverage to a particular direction or sector). The codebook above specifies what the signal intensity will be different at a specific coverage zone defined by the azimuth angle or elevation angular ranges from the transmitter (here, cell tower).
Assume that the first element in the given set, f, indicates the coverage zone from 0 to 10 degrees.
The second element depicts the coverage area between 10 and 20 degrees from the base station.
Additionally, every component in the codebook has directions, or azimuth angle ranges from 0 to 360 degree.
A similar procedure is applicable for mobile stations (MS) to identify the strongest beam between them by determining the optimum path (here, beam) from MS to BS.
2. Digital Beamforming
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Fig: Digital Beamforming
Each antenna element, in this case, is connected to a separate RF chain during digital Beamforming. Filters, mixers, amplifiers, etc., make up RF chains. Each RF chain controls a particular data stream between TX and RX.
Any signal or data stream transmitted by transmitter side antenna T1 is typically received by all receiver side antennas. There are four different user equipment (UEs) or mobile stations shown in the above diagram. All four UEs receive any signal that is sent by antenna T1. Assume that receiver R1 was the only one for which the signal was intended. It will then be regarded as interference for receiver side antennas R1, R2, R3,..., and R8. In this situation, a digital beamforming matrix is crucial to eliminate interference at all undesirable receivers while transmitting the signal from T1. and permit R1 to only receive the signal. The individual data streams between T2 and R2, T3 and R3, and so forth can be assumed similarly.
- - - Analog Beamforming
. - - - Digital Beamforming
. - - Equations related to Spectral Efficiency in Digital Beamforming
. - - - Hybrid Beamforming
. - - Equations related to Spectral Efficiency in Hybrid Beamforming
3. Hybrid Beamforming
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First, we connect multiple antenna elements in hybrid Beamforming to increase gain, which is crucial for today's higher-frequency wireless communication systems. Then, precisely as illustrated in the above figure, we apply digital Beamforming to those RF chains. The key advantages of hybrid Beamforming are that
Less interference than digital Beamforming without sacrificing a significant difference in a MIMO system's throughput.
The transmitted signal has a large amount of gain added by analog Beamforming or beam steering to extend its range.
For lower-dimensional MIMO systems, digital Beamforming works well, but massive MIMO systems are where the future of communication is headed. Compared to digital Beamforming, hybrid Beamforming is less complicated and more cost-effective.