Abstract
In this paper, we propose a feedback scheme of a channel covariance matrix with low overhead for massive multiple-input multiple-output systems. The proposed scheme decomposes the channel covariance matrix into the phase and amplitude parts. For the phase part, the element-wise uniform scalar quantization is performed. For the amplitude part, the following feedback information is generated: a bitmap which denotes a sign of difference between adjacent elements, the first value, an increment, and a decrement. To calculate the elements of the amplitude part, starting from the first value, when a bitmap is 1, the increment is added, otherwise the decrement is added. Simulation results show that the feedback overhead of the proposed scheme can be significantly reduced from 1.92% to 48.33% while the performance of mean square error can be maintained with that of the conventional scheme.
Original language | English |
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Title of host publication | ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks |
Publisher | IEEE Computer Society |
Pages | 714-717 |
Number of pages | 4 |
ISBN (Print) | 9781538646465 |
DOIs | |
Publication status | Published - 2018 Aug 14 |
Event | 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 - Prague, Czech Republic Duration: 2018 Jul 3 → 2018 Jul 6 |
Publication series
Name | International Conference on Ubiquitous and Future Networks, ICUFN |
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Volume | 2018-July |
ISSN (Print) | 2165-8528 |
ISSN (Electronic) | 2165-8536 |
Other
Other | 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 18/7/3 → 18/7/6 |
Bibliographical note
Funding Information:This work was partially supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-0-00181, Development on the core technologies of transmission, modulation and coding with low-power and low-complexity for massive connectivity in the IoT environment) and by the Graduate School of YONSEI University Research Scholarship Grants in 2017.
Publisher Copyright:
© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture