Iterative QR decomposition-based detection algorithms with multiple feedback and dynamic tree search for LDPC-coded 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 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.

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ASIC implementation of a modified QR decomposition for tree search based MIMO detection

2013 IEEE 4th Latin American Symposium on Circuits and Systems (LASCAS) ◽

10.1109/lascas.2013.6519049 ◽

2013 ◽

Cited By ~ 2

Author(s):

C. Gimmler-Dumont ◽

P. Schlafer ◽

N. Wehn

Keyword(s):

Qr Decomposition ◽

Tree Search ◽

Mimo Detection

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Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems

Journal of Electrical and Computer Engineering ◽

10.1155/2018/4034625 ◽

2018 ◽

Vol 2018 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Xinhe Zhang ◽

Yuehua Zhang ◽

Chang Liu ◽

Hanzhong Jia

Keyword(s):

Computational Complexity ◽

Mimo Systems ◽

Optimal Solution ◽

Low Complexity ◽

Search Tree ◽

Spatial Modulation ◽

Algorithm Analysis ◽

Detection Algorithms ◽

Search Order ◽

Ber Performance

In this paper, the authors propose three low-complexity detection schemes for spatial modulation (SM) systems based on the modified beam search (MBS) detection. The MBS detector, which splits the search tree into some subtrees, can reduce the computational complexity by decreasing the nodes retained in each layer. However, the MBS detector does not take into account the effect of subtree search order on computational complexity, and it does not consider the effect of layers search order on the bit-error-rate (BER) performance. The ost-MBS detector starts the search from the subtree where the optimal solution is most likely to be located, which can reduce total searches of nodes in the subsequent subtrees. Thus, it can decrease the computational complexity. When the number of the retained nodes is fixed, which nodes are retained is very important. That is, the different search orders of layers have a direct influence on BER. Based on this, we propose the oy-MBS detector. The ost-oy-MBS detector combines the detection order of ost-MBS and oy-MBS together. The algorithm analysis and experimental results show that the proposed detectors outstrip MBS with respect to the BER performance and the computational complexity.

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Partial Tree Search Assisted Symbol Detection for Massive MIMO Systems

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2020.3022916 ◽

2020 ◽

Vol 69 (11) ◽

pp. 13319-13327

Author(s):

Hoang-Yang Lu ◽

Le-Ping Chang ◽

Hsien-Sen Hung

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Tree Search ◽

Symbol Detection ◽

Partial Tree

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Design and VLSI Implementation of a Reduced-Complexity Sorted QR Decomposition for High-Speed MIMO Systems

Electronics ◽

10.3390/electronics9101657 ◽

2020 ◽

Vol 9 (10) ◽

pp. 1657

Author(s):

Lu Sun ◽

Bin Wu ◽

Tianchun Ye

Keyword(s):

Communication Systems ◽

High Speed ◽

Mimo Systems ◽

Multiple Input Multiple Output ◽

Cmos Technology ◽

Qr Decomposition ◽

Time Sharing ◽

Hardware Complexity ◽

Givens Rotation ◽

Hardware Efficiency

In this article, a low-complexity and high-throughput sorted QR decomposition (SQRD) for multiple-input multiple-output (MIMO) detectors is presented. To reduce the heavy hardware overhead of SQRD, we propose an efficient SQRD algorithm based on a novel modified real-value decomposition (RVD). Compared to the latest study, the proposed SQRD algorithm can save the computational complexity by more than 44.7% with similar bit error rate (BER) performance. Furthermore, a corresponding deeply pipelined hardware architecture implemented with the coordinate rotation digital computer (CORDIC)-based Givens rotation (GR) is designed. In the design, we propose a time-sharing Givens rotation structure utilizing CORDIC modules in idle state to share the concurrent GR operations of other CORDIC modules, which can further reduce hardware complexity and improve hardware efficiency. The proposed SQRD processor is implemented in SMIC 55-nm CMOS technology, which processes 62.5 M SQRD per second at a 250-MHz operating frequency with only 176.5 kilo-gates. Compared to related studies, the proposed design has the best normalized hardware efficiency and achieves a 6-Gbps MIMO data rate which can support current high-speed wireless communication systems such as IEEE 802.11ax.

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