Massive MIMO opens up attractive possibilities for next generation wireless systems with its large number of antennas offering spatial diversity and multiplexing gain. However, the fronthaul link that connects a massive MIMO Remote Radio Head (RRH) and carries IQ samples to the Baseband Unit (BBU) of the base station can throttle the network capacity/speed if appropriate data compression techniques are not applied.

This talk will be focussed on devising scalable fronthaul solutions for Massive MIMO systems that reduce latency and increase capacity, both of which are crucial objectives of 5G NR. We propose different approaches for fronthaul compression for massive MIMO systems in the uplink. We analyse the performance of the two proposed algorithms with respect to compression ratio, error rate and computational complexity against existing methods.