Good neighbor distributed beam scheduling in coexisting multi-RAT networks

Abstract

Spectrum sharing and employing highly directional antennas in the mm-wave bands are considered among the key enablers for 5G networks. Conventional interference avoidance techniques like listen-before-talk (LBT) may not be efficient for such coexisting networks. In this paper, we address a coexistence mechanism by means of distributed beam scheduling with minimum cooperation between spectrum sharing subsystems without any direct data exchange between them. We extend a "Good Neighbor" (GN) principle initially developed for decentralized spectrum allocation to the distributed beam scheduling problem. To do that, we introduce relative performance targets, develop a GN beam scheduling algorithm, and demonstrate its efficiency in terms of performance/complexity trade off compared to that of the conventional selfish (SLF) and recently proposed distributed learning scheduling (DLS) solutions by means of simulations in highly directional antenna mm-wave scenarios.

Good Neighbor Alternative to Best Response and Machine Learning Based Beamforming and Power Adaptation for MIMO Ad Hoc Networks

“…This allows a trade-off between the equilibrium and transient performance leading to controllable convergence behavior without any explicit communications between coexisting subsystems. Application of GN self-organization is addressed in decentralized spectrum sharing in cognitive radio networks [10], [11], and distributed beam scheduling in coexisting multi-RAT networks [12].…”

Spectrum Sharing With Decentralized Occupation Control in Rule Regulated Networks

“…The GN resource allocation could be considered as a general alternative to the selfish network self-organization, e.g. as illustrated in[23] in the downlink beamforming scheduling problem for coexisting multi-RAT networks.…”