Abstract
In this paper, an effective low complexity generalized spatial modulation (GenSM) scheme with transmit antenna grouping is proposed for massive multi-input multi-output (MIMO) system to deal with the channel correlation among transmit antennas. In the proposed scheme, all transmit antennas are divided into several equal-sized groups, and spatial modulation (SM) is carried out to select one active antenna in each group independently. Two different grouping methods, i.e., block grouping and interleaved grouping, are introduced to optimize the error performance in low and high signal-to-noise ratio (SNR) region, respectively. In consideration of the large amount of transmit antennas in a massive MIMO system, both linear and 2-dimensional transmit antenna arrays are considered in our design. To evaluate the performance, a closed-form expression of the average bit error probability (ABEP) upper bound is derived for all proposed grouping methods and Monte-Carlo simulations are conducted to verify the analysis and reveal the performance gain of the proposed scheme in terms of bit error rate (BER) in comparison with conventional GenSM.
| Original language | English |
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| Title of host publication | 2017 IEEE International Conference on Communications, ICC 2017 |
| Editors | Merouane Debbah, David Gesbert, Abdelhamid Mellouk |
| ISBN (Electronic) | 9781467389990 |
| DOIs | |
| State | Published - Jul 28 2017 |
| Event | 2017 IEEE International Conference on Communications, ICC 2017 - Paris, France Duration: May 21 2017 → May 25 2017 |
Publication series
| Name | IEEE International Conference on Communications |
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| ISSN (Print) | 1550-3607 |
Conference
| Conference | 2017 IEEE International Conference on Communications, ICC 2017 |
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| Country/Territory | France |
| City | Paris |
| Period | 5/21/17 → 5/25/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Funding
Our future work will focus on antenna arrays with more realistic channel parameters [20] and the optimization of the group size and other system configurations. VI. ACKNOWLEDGEMENT This work was jointly supported by the National Natural Science Foundation of China (Grant No. 61622101 and 61571020), the Ministry National Key Research and Development Project under Grant 2016YFE0123100, the National 973 project (Grant No. 2013CB336700), the open research fund of the State Key Laboratory of Integrated Services Networks, Xidian University (Grant No. ISN18-14), and the National Science Foundation under grant number CNS-1343189.
| Funders | Funder number |
|---|---|
| National Science Foundation Arctic Social Science Program | CNS-1343189 |
| National Science Foundation Arctic Social Science Program | |
| arrays | |
| Applied Basic Research Key Project of Yunnan | 2016YFE0123100, 2013CB336700 |
| Applied Basic Research Key Project of Yunnan | |
| CNS-1343189 | |
| Applied Basic Research Key Project of Yunnan | |
| Shanghai Key Laboratory of Navigation and Location Based Services | |
| National Natural Science Foundation of China (NSFC) | 61571020, 61622101 |
| National Natural Science Foundation of China (NSFC) | |
| Xidian University | ISN18-14 |
| Xidian University |
ASJC Scopus subject areas
- Computer Networks and Communications
- Electrical and Electronic Engineering