Faculty Sponsor's Department(s):
A key aspect of modern communications engineering focuses on maximizing data throughput. When utilizing numerous antennas for transmission and reception, we can send multiple data streams and reuse the same frequency and time resources via spatial multiplexing. By employing a high-frequency and small-wavelength carrier, many antennas can be ﬁt on a small platform with Rayleigh spacing, thereby increasing the spatial degrees of freedom in a line-of-sight MIMO link. However, due to the dependence of the MIMO channel on link distance, throughput degradation may be observed at smaller distances due to “mode collapse.” We aim to prevent mode collapse by introducing extra antennas (spatial redundancy) at the receiver and rethinking the antenna placement to maximize the robustness of our system to link distance variation. We simulated a MIMO array with 4 transmit and 9 receive antennas calculating how the channel condition varies with diﬀerent receive antenna conﬁguration. Upon utilizing singular value decomposition on our channel matrix, we calculate the ratio of the weakest and strongest eigenmodes of the channel, as well as overall channel capacity as a function of link distance. Our simulations indicate that uniform antenna placement provides better nominal performance while more randomized conﬁgurations show higher robustness and prevent mode collapse at all distances.