Throughput Degradation Due to Mobility in Millimeter Wave Communication Systems Using Random Beamforming

Random Beamforming in Mobile mmWave Systems: Performance Evaluation and Parameters Optimization

“…The first part of our work is studying the mobility effect from different perspective [14]. Taking the same assumptions in [2] and [4] for system model and assuming we have many UE's in the system and each of them will have various mobility states (fixed, walking, running, biking, or riding a moving car).…”

“…These factors include the beam width (of the beamforming), the distance between BS and the mobile UE (as a random variable), the mobility orientation (or the movement direction of each UE), and the maximum shift in UE position during the round trip time (RTT) of the messages during the beamforming and data transmission time. The effect of each of these factors was studied alone and then they were combined together in a closed form expression that describes the throughput degradation results from UE mobility [14]. The other possible effects of mobility like blockage (both from the user itself (self blockage) or from other obstacles in the environment), the doppler shift results from horizontal and vertical movement of UE during mobility, and user scheduling if there are many users in each beam coverage areas are good directions for further future work.…”

“…After studying the mobility effect and derive it both mathematically and through extensive simulation in [14], it was obvious that some systems parameters need to be optimized for different operation scenarios. The frame duration and the beam angle (or beam width, as they will be used interchangeably throughout the paper) for RBF in mobile scenarios was studied as well in [17].…”

“…Taking in consideration the typical coverage distance for Base Stations in an Ultra Dense Networks [23] (i.e. no more than 200 meters), and the results of the work in [14], we derived the best frame duration and the beam width for each outage probability [17].…”

“…Frame duration optimization is also considered in this paper for the MIMO systems that uses Random Beamforming algorithm and mmWave frequencies. In the optimization process, the derived expected degradation (the outage probability) resulted from the UE mobility during the communication which was published in [14] is now used for parameter optimization of the system and for different scenarios.…”