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2019 | OriginalPaper | Chapter

4. Massive Access with Channel Reciprocity

Author : Xiaoming Chen

Published in: Massive Access for Cellular Internet of Things Theory and Technique

Publisher: Springer Singapore

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Abstract

In this chapter, we propose a comprehensive fully non-orthogonal communication framework for cellular IoT in TDD mode. Firstly, we design a fully non-orthogonal communication scheme which consists of non-orthogonal channel estimation and non-orthogonal multiple access. Then, we analyze the performance of the proposed fully non-orthogonal communication, and derive a tight lower bound on the spectral efficiency in terms of key system parameters and channel conditions. Meanwhile, several novel insights are provided on spectral efficiency via asymptotic analysis in three important cases, i.e., a large number of base station (BS) antennas, a high BS transmit power, and perfect channel state information (CSI) at the BS. Finally, we optimize the performance of the proposed fully non-orthogonal communication and present two simple but efficient optimization algorithms for maximizing the weighted sum of spectral efficiency. Extensive simulation results validate the effectiveness of the proposed schemes.

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previous chapter Massive Access with Channel Quantization Codebook
next chapter Massive Access with Channel Statistical Information
Footnotes
1
The proposed fully non-orthogonal communication framework can be extended to a multi-cell scenario directly. We will study the multi-cell case later.
 
2
In practical systems, due to the physical size limitation, the IoT device is in general equipped with a single antenna [7, 12]. If the UE has multiple antennas, some signal receiving schemes, e.g., antenna selection, can be adopted to enhance the performance. Then, it is equivalent to the case of a single-antenna UE.
 
3
In practice, the large-scale antenna array at the BS might be correlated in some scenarios. In general, the channel from the BS to the UEm,n can be represented as R m,n h m,n, where R m,n is the correlation matrix and h m,n is the channel small-scale fading vector with i.i.d. zero mean and unit variance complex Gaussian distributed random variable. Since the correlation matrix R m,n usually varies slowly compared to h m,n, it is reasonably assumed that R m,n is known at both the BS and the UE. Mathematically, the impact of the correlation matrix R m,n is equivalent to that of the path loss α m,n in the case of i.i.d. channel, thus the proposed fully non-orthogonal transmission scheme is also applicable in the scenario of channel correlation.
 
4
By measuring a large number of samples in a long training time, the residual interference over i.i.d. Rayleigh channels can be accurately approximated using a Gaussian distribution due to the central limit theorem and its variance is a function of the received power [21]. Then, by comparing the powers of the residual interference and the received signal, the coefficient η m,n can be obtained.
 
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Metadata
Title
Massive Access with Channel Reciprocity
Author
Xiaoming Chen
Copyright Year
2019
Publisher
Springer Singapore
Book
Massive Access for Cellular Internet of Things Theory and Technique

Print ISBN: 978-981-13-6596-6

Electronic ISBN: 978-981-13-6597-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-13-6597-3_4