Millimeter wave spectrum for 5G cellular networks
The era of operating wireless systems at the millimeter wave spectrum, ranging from 30 GHz to 300 GHz, is coming. With several gigahertz potential spectrum, mmWave will be used for access channels in 5G cellular networks. The Federal Communications Commission (FCC) in the USA has been considering making rules to authorize mobile operations in certain mmWave band with county-size licenses.
MmWave cellular networks will operate in a different manner from conventional cellular systems below 6 GHz: for one thing, measurements reveal different propagation conditions, , e.g. the sensitivity to blockage, at mmWave from those at sub-6 GHz frequencies; for another, mmWave cellular networks will apply different architectures, e.g. analog or hybrid directional beamforming with large arrays, for signal processing. Consequently, new mathematical models are required for analyzing mmWave cellular networks, as previous ones for low frequencies do not directly apply.
Our group has made breakthroughs in building up analytical models for mmWave cellular networks, using stochastic geometry. The proposed model takes account for key mmWave features, including the blockage effects from buildings and human bodies, and the use of directional beamforming. Based on the model, the distributions of the SINR and rate in mmWave cellular systems were derived in analytical expressions. The results showed that given the blockage distributions, the mmWave performance is much sensitive to the base station density: comparable SINR coverage to that in the low frequency system can be achieved with sufficient base station density, which translates into much higher rate due to the larger bandwidth.
Another application of the mmWave system model is to compare the performance of massive MIMO in sub-6 GHz and mmWave bands using a common framework. Our analysis showed that in terms of the throughput per unit area, the optimal carrier frequency to deploy massive MIMO depends on the base station density: mmWave outperforms in dense base station networks, while its performance degrades with sparse base stations due to the coverage holes resulted from blockage effects.