Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems
Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies h...
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MDPI AG
2020-06-01
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| Online Access: | https://www.mdpi.com/2078-2489/11/6/301 |
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| author | Samarendra Nath Sur Rabindranath Bera Akash Kumar Bhoi Mahaboob Shaik Gonçalo Marques |
| author_facet | Samarendra Nath Sur Rabindranath Bera Akash Kumar Bhoi Mahaboob Shaik Gonçalo Marques |
| author_sort | Samarendra Nath Sur |
| collection | DOAJ |
| description | Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin. |
| first_indexed | 2024-03-10T19:23:14Z |
| format | Article |
| id | doaj.art-d54bea3873c643b49ad59ce08b472fe5 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T19:23:14Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-d54bea3873c643b49ad59ce08b472fe52023-11-20T02:48:38ZengMDPI AGInformation2078-24892020-06-0111630110.3390/info11060301Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO SystemsSamarendra Nath Sur0Rabindranath Bera1Akash Kumar Bhoi2Mahaboob Shaik3Gonçalo Marques4Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, Sikkim, IndiaDepartment of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, Sikkim, IndiaDepartment of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, Sikkim, IndiaDepartment of Electrical Engineering, Muffakham Jah College of Engineering and Technology, Hyderabad 500034, IndiaInstituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, PortugalMassive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin.https://www.mdpi.com/2078-2489/11/6/301MIMOZFMMSELLR-ZFLLR-MMSEKZ-ZF |
| spellingShingle | Samarendra Nath Sur Rabindranath Bera Akash Kumar Bhoi Mahaboob Shaik Gonçalo Marques Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems Information MIMO ZF MMSE LLR-ZF LLR-MMSE KZ-ZF |
| title | Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems |
| title_full | Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems |
| title_fullStr | Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems |
| title_full_unstemmed | Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems |
| title_short | Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems |
| title_sort | capacity analysis of lattice reduction aided equalizers for massive mimo systems |
| topic | MIMO ZF MMSE LLR-ZF LLR-MMSE KZ-ZF |
| url | https://www.mdpi.com/2078-2489/11/6/301 |
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