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Robust signal processing for asynchronous distributed massive MIMO

Robust signal processing for asynchronous distributed massive MIMO
用于异步分布式大规模 MIMO 的鲁棒信号处理
批准号:
502013-2016
负责人:
Shahbazpanahi, Shahram
金额:
$3.9万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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英文摘要
In this NSERC Collaborative Research and Development Grant proposal, we propose to study centralized and de-centralized signal processing techniques for asynchronous distributed massive multiple input multiple output (MIMO) systems. Distributed massive MIMO systems are comprise of many base stations (BSs) each of which is equipped with multiple antennas. Such systems benefit from the advantages offered by massive MIMO systems (where the effects of fast fading and uncorrelated noise are vanished) while allowing distributed processing and exploiting user diversity.****In our study, we focus on three aspects of distributed massive MIMO systems, namely energy efficiency, latency, and computational complexity. In traditional models for massive MIMO communication systems, it is often assumed that different users/base stations in the network are time-synchronized at the symbol level. This assumption, however, may not be realistic due to the fact that different users are located at different distances from the massive MIMO base stations. To the best of our knowledge, the published results on distributed massive MIMO ignore two facts. The first fact which is often ignored is that the signals transmitted by one user device will very likely arrive at different massive MIMO BSs with different delays. The second fact which is also ignored is that signals transmitted by different massive MIMO BSs also arrive at one receiver with different delays. For example, in coordinated multi-point (CoMP) scheme with many base stations and with possibly many antennas at each base station, these aforementioned delays need to be taken into account. Due to these delays, the end-to-end channel can no longer be modeled as a frequency-flat link. Indeed, the end-to-end channel is best modeled with a multi-path (frequency selective) impulse response. Such a view point on the end-end-end channel makes the equalization of this channel inevitable, whether it will be a single-carrier equalization scheme or a multi-carrier one. **
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