• Title/Summary/Keyword: Random beamforming

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On the Multiuser Diversity in SIMO Interfering Multiple Access Channels: Distributed User Scheduling Framework

  • Shin, Won-Yong;Park, Dohyung;Jung, Bang Chul
    • Journal of Communications and Networks
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    • v.17 no.3
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    • pp.267-274
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    • 2015
  • Due to the difficulty of coordination in the cellular uplink, it is a practical challenge how to achieve the optimal throughput scaling with distributed scheduling. In this paper, we propose a distributed and opportunistic user scheduling (DOUS) that achieves the optimal throughput scaling in a single-input multiple-output interfering multiple-access channel, i.e., a multi-cell uplink network, with M antennas at each base station (BS) and N users in a cell. In a distributed fashion, each BS adopts M random receive beamforming vectors and then selects M users such that both sufficiently large desired signal power and sufficiently small generating interference are guaranteed. As a main result, it is proved that full multiuser diversity gain can be achieved in each cell when a sufficiently large number of users exist. Numerical evaluation confirms that in a practical setting of the multi-cell network, the proposed DOUS outperforms the existing distributed user scheduling algorithms in terms of sum-rate.

Compressed Sensing Techniques for Millimeter Wave Channel Estimation (밀리미터파 채널 추정을 위한 압축 센싱 기법)

  • Han, Yonghee;Lee, Jungwoo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.1
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    • pp.25-30
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    • 2017
  • Millimeter wave (mmWave) bands are expected to improve date rate of 5G systems due to the wide available bandwidth. While severe path loss in those bands has impeded the utilization, short wavelength enables a large number of antennas packed in a compact form, which can mitigate the path loss. However, estimating the channel with a conventional scheme requires a huge training overhead, hence an efficient estimation scheme operating with a small overhead needs to be developed. The sparsity of mmWave channels caused by the limited scatterers can be exploited to reduce the overhead by utilizing compressed sensing. In this paper, we introduce compressed sensing techniques for mmWave channel estimation. First, we formulate wideband channel estimation into a sparse recovery problem. We also analyze the characteristics of random measurement matrix constructed using quantized phase shifters in terms of mutual incoherence.