Title:Low-complexity User Scheduling Framework for mmWave Hybrid Beam-forming OFDM System under Non-ideal CSI
Volume: 18
Issue: 2
Author(s): Jia Liu*Bo Wang
Affiliation:
- School of Information and Communication, Guilin University of Electronic Technology, Guilin, China
- Samsung
Research China-Beijing (SRC-B), Beijing, China
Keywords:
Hybrid beam-forming, OFDM, user scheduling, RBG allocation, non-ideal CSI, machine learning.
Abstract:
Introduction: User scheduling in millimeter-wave (mmWave) multi-user hybrid
beam-forming Orthogonal Frequency Division Multiplexing (OFDM) systems involves the
joint optimization of resource block group (RBG) allocation, beam pairing, and user selection.
However, choosing the optimal scheduled User Equipment (UE), allocated RBGs, and communicating
beams in practical mmWave hybrid beam-forming systems with non-ideal Channel
State Information (CSI) remains challenging.
Methods: In this paper, we propose a low-complexity user scheduling framework. On one
hand, two user classification methods are proposed under non-ideal CSI, assisted by beam
search and RBG allocation respectively. On the other hand, in order to ensure both the
throughput and fairness performance, a novel user selection scheme, called weighted user selection
based on feedback threshold (WUSFT) scheme is proposed, and approximate closedform
expression of fairness index for both full feedback and feedback based on threshold are
derived. Our proposed methods consist of three steps. First, RBGs are allocated based on the
maximum received signal power (MRSP) of each user on each RBG, utilizing quasiomnidirectional
beams. In the second step, the communicating beams are further searched to
achieve the MRSP with the allocated RBG.
Results: Finally, the allocated RBG, or the determined beam information obtained through the
beam search, is used to represent the correlation of user channels and classify the UEs into
groups. Only UEs whose reported factor is not less than the feedback threshold will report received
information. This simplifies the operation of user scheduling. Moreover, simulation results
demonstrate that our proposed schemes can achieve more than 92.3% of the sum rate performance
of exhaustive search methods while maintaining relatively low complexity.
Conclusion: In addition, the user feedback overhead (FO) reduces obviously, especially with
large UE number.
