Adaptive Beam Sweeping With Supervised Learning

Lei, WanluKTH,Teknisk informationsvetenskap,Ericsson Inc, GAIA, Santa Clara, CA 95054 USA. (författare)

QC 20230130
Utilizing millimeter-wave (mmWave) frequencies for wireless communication in mobile systems is challenging since continuous tracking of the beam direction is needed. For the purpose, beam sweeping is performed periodically. Such approach can be sufficient in the initial deployment of the network when the number of users is small. However, a more efficient solution is needed when lots of users are connected to the network due to higher overhead consumption. We explore a supervised learning approach to adaptively perform beam sweeping, which has low implementation complexity and can improve cell capacity by reducing beam sweeping overhead. By formulating the beam tracking problem as a binary classification problem, we applied supervised learning methods to solve the formulated problem. The methods were tested on two scenarios: ray-tracing outdoor scenario and over-the-air (OTA) testing dataset from Ericsson. Both experimental results show that the proposed methods significantly increase cell throughput comparing with existing exhaustive sweeping and periodical sweeping strategies.

Lu, ChenguangEricsson Res, S-16483 Stockholm, Sweden. (författare)
Huang, YeziEricsson Res, S-16483 Stockholm, Sweden. (författare)
Rao, JingEricsson AB, BNEW DNEW, S-16483 Stockholm, Sweden. (författare)
Xiao, Ming,1975-KTH,Teknisk informationsvetenskap(Swepub:kth)u1iq6n9a (författare)
Skoglund, Mikael,1969-KTH,Teknisk informationsvetenskap(Swepub:kth)u1dbnyps (författare)
KTHTeknisk informationsvetenskap (creator_code:org_t)

Ingår i:IEEE Wireless Communications Letters: Institute of Electrical and Electronics Engineers (IEEE)11:12, s. 2650-26542162-23372162-2345

Av författaren/redakt...: Lei, Wanlu; Lu, Chenguang; Huang, Yezi; Rao, Jing; Xiao, Ming, 1975 ...; Skoglund, Mikael ...

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