Import the required city geometry into Ansys Electronics Desktop (AEDT). Choose base-station and user device locations. Select antenna type from the parametric antennas dictionary or design your own antennas/arrays in HFSS.
Configure all sources as either transmitters or receivers. Create a frequency sweep set-up with a specified center frequency, bandwidth and number of subcarriers. Assign subcarriers and transmit powers to each transmitter.
Specify noise power and transmitter sources to be decoded. Calculate mutual information for linear and or optimal decoding strategies.
For this workflow we use a base-station with 3 antenna arrays each covering a single 120 degrees sector. For each individual array we use a connected slot array with 16 elements backed by a pec plate. The array is designed at 5GHz with elements spaced at half-wavelength. The city geometry is imported from open street maps with latitude and longitude specified to represent the city center of Los Angeles. The import consists of buildings, roads and terrain each assigned as concrete. The locations are chosen to place base-stations at the top of the buildings. For the user-equipment (UE) we use omnidirectional Hertzian dipole uniform linear antenna arrays with 2 antenna elements. The 4 users are placed on the road at different locations. Each individual UE to base-station link is 2x16 MIMO system.
Consider an uplink system in which the 4 users are transmitting to the base-station utilizing orthogonal frequency division multiple access scheme. The 4 UE devices are operating over the frequency band of 100Mhz centered around 5GHz carrier frequency. As an example, we consider a system with 10 subcarriers where each subcarrier has a dedicated 10MHz of bandwidth. We assume that users 1 and 3 share the same first 5 subcarriers in the lower part of the band while users 2 and 4 share the other 5 subcarriers in the upper part of the band. The image on the right displays the locations of the users 1 and 3 interfering over the first 5 subcarriers as well as the base station sector which was designed to connect the two users to the cellular network. The next section will demonstrate how this particular sector base-station achieves the highest rate for the two UEs.
Assuming -90dBm of noise power at the base station and 100mW of transmit power for the UEs (50mW per antenna), we calculate the MIMO capacity of user 3 over each subcarrier to every one of the base stations. As can be seen base-station 4 has the best connection to user 3 with about 110 Mb/s of rate for each subcarrier which is equivalent to about 11 bits per transmission and would require 2048 QAM modulation order. The base-station with the best connection is also displayed above in the uplink system configuration section. This is intuitively expected from the geometric set-up as that sector base station has its main beam pointing at the two UEs. Also notice that even while the two UEs are interfering over the subcarriers at the base station, with a MIMO array and optimal receiver processing the interference is mitigated and very high rate per symbol is achieved.
Choosing base-station 4 as our choice to connect user 3, we compare 3 linear detection schemes to the ultimate achievable rate limit. The 3 linear detection schemes are maximal ratio combining (MRC), zero forcing (ZF) and linear minimum mean squared error (LMMSE) detection. As is expected the LMMSE is the best linear detection scheme. LMMSE utilizes the knowledge of the interference channel to obtain the best estimate of the transmitted symbols before decoding. Yet the rate achieved by LMMSE is significantly lower than the ultimate achievable rate due to its symbol by symbol decoding structure. ZF and MRC detectors fail to deliver good data rates because of strong interference from user 1.
When we plot mutual information vs transmit power we expect ZF receiver to be inferior to MRC at low transmit powers and to become increasingly better at higher transmit powers. In the ideal scenario with no noise/interference zero-forcing receiver can perfectly invert the channel and so it would become equivalent to LMMSE detector. On the other hand at low transmit powers, MRC and LMMSE receivers are essentially equivalent. Both of those intuitive results are verified in the workflow.
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