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Coordinated multicell beamforming for massive multiple-input multiple-output systems based on uplink-downlink duality

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IET COMMUNICATIONS 2016年第17期10卷 2380-2390页

作者： He, Shiwen Huang, Yongming Shi, Yanru Qi, Chenhao Jin, Shi Yang, Luxi Southeast Univ Sch Informat Sci & Engn Nanjing 210096 Jiangsu Peoples R China

This paper studies joint beamforming and power allocation for multicell multiuser multi-antenna systems with the objective of maximising the minimum signal-to-interference-plus-noise ratio (max-min SINR). The authors first consider developing an iterative algorithm to achieve the optimal performance by extending the uplink-downlink duality for finite-scale wireless communication systems. The solution is then generalised to achieve the asymptotically optimal multicell beamforming with the aim to reduce the overhead of signalling exchange between coordinated base stations based on large dimension random matrix theory. Based on that, an efficient multicell beamforming algorithm is proposed to asymptotically achieve the max-min SINR. To further solve the complexity issue of large dimensional matrix inversion involved in the calculation of beamforming vectors, they propose a low-complexity beamforming calculator based on truncated polynomial expansion approach. Numerical results validate the effectiveness of the authors' proposed algorithms and show that they can achieve the optimal or asymptotically optimal performance in a massive multi-input multi-output system with low complexity and small backhaul overhead.

关键词： array signal processing MIMO communication radiofrequency interference telecommunication signalling matrix algebra multiuser detection iterative methods coordinated multicell beamforming massive multiple-input multiple-output systems uplink-downlink duality joint beamforming power allocation multicell multiuser multiantenna systems signal-to-interference-plus-noise ratio SINR iterative algorithm finite-scale wireless communication systems random matrix theory

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Efficient and low-complexity matrix inversion scheme for massive multiple-input multiple-output systems using rapid numerical algorithms

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JOURNAL OF ENGINEERING-JOE 2019年第10期2019卷 7244-7249页

作者： Mukubwa, Emmanuel Sokoya, Oludare A. Durban Univ Technol Dept Elect POB 1334 ZA-4000 Durban South Africa

Performances of the regularised zero forcing (RZF) precoder, rapid numerical algorithm (RNA) precoder and the truncated polynomial expansion (TPE) Precoder are compared and analysed for massive multiple-input multiple-output (MIMO) wireless system in a downlink scenario. The achievable data rates, bit error rates and signal-to-interference-to-noise ratio were investigated. The simulated results agree with the theory of massive MIMO system. Also, the RZF precoder and the RNA precoder perform better in comparison to TPE precoder.

关键词： linear codes precoding interference suppression matrix inversion polynomials wireless channels MIMO communication radiofrequency interference error statistics massive multiple-input multiple-output systems rapid numerical algorithms rapid numerical algorithm precoder truncated polynomial expansion Precoder massive multiple-input multiple-output wireless system achievable data rates massive MIMO system RZF precoder RNA precoder TPE precoder low-complexity matrix inversion scheme

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massive MIMO CSI reconstruction using CNN-LSTM and attention mechanism

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IET COMMUNICATIONS 2020年第18期14卷 3089-3094页

作者： Zhang, Zufan Zheng, Yue Gan, Chenquan Zhu, Qingyi Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China Chongqing Key Lab Mobile Commun Technol Chongqing 400065 Peoples R China Minist Educ Engn Res Ctr Mobile Commun Chongqing 400065 Peoples R China Chongqing Univ Posts & Telecommun Sch Cyber Secur & Informat Law Chongqing 400065 Peoples R China

In massive multiple-input multiple-output (MIMO) systems, the channel state information (CSI) feedback enables performance gain in frequency division duplex networks. However, with the increase in the number of antennas, the feedback overhead of CSI will also enhance. To this end, this study addresses the issue of massive MIMO CSI reconstruction using convolutional neural network (CNN), long short-term memory (LSTM) and attention mechanism, and proposes an efficient network architecture (denoted as CNN-LSTM-A). To achieve a compromise between performance and complexity, the proposed method significantly reduces the number of training parameters by utilising a single-stage network rather than a multiple-stage network. Finally, simulation results show that the authors method can reduce the feedback overhead of CSI effectively, and achieves better performance in terms of CSI compression and recovery accuracy compared with existing state-of-the-art methods.

关键词： MIMO communication convolutional neural nets channel estimation learning (artificial intelligence) recurrent neural nets massive MIMO CSI reconstruction attention mechanism massive multiple-input multiple-output systems channel state information feedback frequency division duplex networks convolutional neural network network architecture CNN-LSTM-A single-stage network multiple-stage network antenna number CSI feedback overhead long short-term memory CSI compression

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Channel estimation for FDD multi-user massive MIMO systems: a greedy approach based on user clustering

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IET SIGNAL PROCESSING 2019年第9期13卷 778-786页

作者： Azizipour, Mohammad Javad Mohamed-pour, Kamal KN Toosi Univ Technol Fac Elect Engn 470 Mirdamad Ave West Tehran 19697 Iran

Obtaining channel state information (CSI) at the transmitter side is essential to take advantage of spectral and energy efficiency in massive multiple-input multiple-output systems. In particular, due to a large number of antennas at the base station (BS) side, the required pilots for downlink channel estimation and the following CSI feedback in the uplink path would be prohibitively large when the system employs frequency-division duplex protocol for data transmission. In this study, the authors propose a novel compressed sensing algorithm which exploits the commonly shared sparsity among nearby users to reduce the estimation error and the number of assigned pilots accordingly. Moreover, to gather users' channel with common sparsity, a clustering procedure is introduced, which groups active users located in the cell according to their mean angle of arrivals received by the uplink signals at the BS antenna array. After clustering users properly, the proposed algorithm can exploit shared support set existing in each cluster efficiently, thereby improving CSI estimation performance. Numerical results demonstrate that the clustering idea along with the proposed algorithm, outperforms other solutions, and is capable of approaching the performance bound when the transmit power is increased.

关键词： MIMO communication compressed sensing antenna arrays channel estimation frequency division multiplexing protocols multi-access systems direction-of-arrival estimation greedy algorithms pattern clustering FDD multiuser massive MIMO systems greedy approach user clustering channel state information spectral energy efficiency massive multiple-input multiple-output systems base station side downlink channel estimation CSI feedback uplink path frequency-division duplex protocol data transmission novel compressed sensing algorithm estimation error clustering procedure uplink signals BS antenna array CSI estimation performance clustering idea

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Joint spatial modulation and beamforming based on statistical channel state information for hybrid massive MIMO communication systems

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IET COMMUNICATIONS 2019年第10期13卷 1458-1464页

作者： Zhang, Mingxuan Miao, Weiwei Shen, Yiting Huang, Jin Zhang, Shaqian Zeng, Zeng Tang, Hao Wu, Liang Zhang, Zaichen Dang, Jian State Grid Jiangsu Elect Power Co Informat & Telecommun Branch Nanjing 210024 Jiangsu Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China

Spatial modulation is a promising transmission scheme for massive multiple-input multiple-output (MIMO) systems to improve energy efficiency. In this study, considering the low-complexity hybrid structure, the authors propose a joint spatial modulation and beamforming scheme for a hybrid massive MIMO system in both single user and multi-user scenarios. Specifically, a design criterion of the channel control parameter is provided to reduce the high correlation among different channel coefficients in the hybrid massive MIMO system. In addition, with the statistical channel state information acquired at the base station, the optimum analogue beamforming vectors are designed with the goal of maximising the signal to leakage and noise ratio in the multi-user scenario. Furthermore, the upper bound, the lower bound as well as the closed form approximation of achievable spectral efficiency of the proposed scheme are derived for both single user and multi-user scenarios. Numerical simulation results demonstrate that the proposed scheme outperforms the conventional MIMO scheme.

关键词： array signal processing MIMO communication antenna arrays optimum analogue beamforming vectors multiuser scenario single user conventional MIMO scheme joint spatial modulation statistical channel state information hybrid massive MIMO communication systems promising transmission scheme massive multiple-input multiple-output systems low-complexity hybrid structure beamforming scheme hybrid massive MIMO system channel control parameter different channel coefficients

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Low-complexity linear massive MIMO detection based on the improved BFGS method

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IET COMMUNICATIONS 2022年第14期16卷 1699-1707页

作者： Li, Lin Hu, Jianhao Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China Qinghai Normal Univ Xining Qinghai Peoples R China

Linear minimum mean square error (MMSE) detection achieves a good trade-off between performance and complexity for massive multiple-input multiple-output (MIMO) systems. To avoid the high-dimensional matrix inversion involved, MMSE detection can be transformed into an unconstrained optimization problem and then solved by efficient numerical algorithms in an iterative way. Three low-complexity Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton methods are proposed to iteratively realize massive MIMO MMSE detection without matrix inversion. The complexity can be reduced from O(K3)$\mathcal {O}(K<^>massive)$ to O(LK2)$\mathcal {O}(LK<^>multiple)$, where K and L denote the number of users and iterations, respectively. Leveraging the special properties of massive MIMO, the authors first explore a simplified BFGS method (named S-BFGS) to alleviate the computational burden in the search direction. For lower complexity, BFGS method with the unit step size (named U-BFGS) is presented subsequently. When the base station (BS)-to-user-antenna ratio (BUAR) is large enough, the two proposed BFGS methods can be integrated (named U-S-BFGS) to further reduce complexity. In addition, an efficient initialization strategy is devised to accelerate convergence. Simulation results verify that the proposed detection scheme can achieve near-MMSE performance with a small number of iterations L as low as 2 or 3.

关键词： base station-to-user-antenna ratio MIMO communication matrix inversion least mean squares methods optimisation linear minimum mean square error detection simplified BFGS method computational complexity massive MIMO MMSE detection Newton method high-dimensional matrix inversion low-complexity Broyden-Fletcher-Goldfarb-Shanno quasiNewton methods detection scheme improved BFGS method near-MMSE performance iterative methods U-BFGS convergence of numerical methods maximum likelihood detection unconstrained optimization problem low-complexity linear massive MIMO detection massive multiple-input multiple-output systems

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Eradication of pilot contamination and zero forcing precoding in the multi-cell TDD massive MIMO systems

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IET COMMUNICATIONS 2017年第13期11卷 2027-2034页

作者： Ali, Sajjad Chen, Zhe Yin, Fuliang Dalian Univ Technol Sch Informat & Commun Engn Dalian Peoples R China

In massive multiple-input multiple-output (M-MIMO) systems, the base station (BS) estimates the downlink and uplink channels using the uplink pilot training in conjunction with channel reciprocity property of time division duplex (TDD) operation. However, this channel estimation is contaminated due to the use of non-orthogonal pilot sequences for the uplink training in neighbouring cells that results in inter-cell interference. This study proposes an effective pilot contamination elimination scheme along with zero forcing precoding for multi-cell TDD M-MIMO systems. In the proposed scheme, each BS is assigned with a specific orthogonal variable spreading factor (OVSF) code row and a set of Zadoff-Chu (ZC) sequences are used for uplink pilot training. Then, the set of ZC sequences is multiplied element-wise at each BS with its OVSF code row to generate the orthogonality among the pilot sequences across the neighbouring cells. The proposed method can promise uncontaminated channel estimation and interference free downlink transmission without requiring the knowledge of the channels' second-order statistics and without increasing the training overhead by a factor equal to the number of interfering cells. The simulation results authenticate the effectiveness and superiority of the proposed scheme over other schemes.

关键词： precoding MIMO communication channel estimation statistical analysis zero forcing precoding multicell TDD massive MIMO systems massive multiple-input multiple-output systems uplink pilot training channel reciprocity property channel estimation time division duplex operation pilot contamination elimination scheme orthogonal variable spreading factor code row OVSF code row Zadoff-Chu sequences interference free downlink transmission second-order statistics

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Multi-cell MMSE data detection for massive MIMO: new simplified bounds

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IET COMMUNICATIONS 2019年第15期13卷 2386-2394页

作者： Alwakeel, Ahmed S. Mehana, Ahmed Hesham KCST Univ Dept Elect & Commun Engn Kuwait Kuwait Cairo Univ Dept Elect & Elect Commun Engn Giza Egypt

In this study, the authors analyse and provide new insights into the problem of multi-cell minimum mean square error (MMSE) detector in massive multiple-input multiple-output (MIMO) systems. Their system combines pilot hopping and pilot reuse strategy in the multi-cell *** obtain a deterministic expression of rate bounds of the uplink system when MMSE is used for channel estimation and data detection. Their result is different from the existing MMSE bounds in massive MIMO literature in that they obtain an achievable rate that is simply a scaled version of that of the matched filter (MF) detection, i.e. the achievable rate of the MF detection can be scaled with a constant, which is a function of the number of antennas and users as well as the power allocation to directly obtain the achievable rate of the MMSE detection. This new finding saves a significant amount of work needed when analysing MMSE detection in massive MIMO since it reduces the problem to obtaining simpler results (using MF analysis) and then extending the result to the MMSE case in a straightforward manner. Simulation results show how tight the achievable rate bound to the actual one at a large number of BS antennas.

关键词： channel estimation MIMO communication mean square error methods matched filters antenna arrays cellular radio rate bounds uplink system MMSE detector massive MIMO literature matched filter detection MF detection MMSE case multicell MMSE data detection massive multiple-input multiple-output systems pilot hopping pilot reuse strategy MMSE channel estimation multicell minimum mean square error detector

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Location-aided channel tracking and downlink transmission for HST massive MIMO systems

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IET COMMUNICATIONS 2017年第13期11卷 2082-2088页

作者： Zhang, Cheng Zhang, Jing Huang, Yongming Yang, Luxi Southeast Univ Sch Informat Sci & Engn Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China

In massive multiple-input multiple-output (MIMO) high-speed train (HST) wireless communication systems (WCS), due to the large-dimension and rapidly time-varying property, channel tracking rather than conventional channel estimation is more feasible. Due to the non-linear channel variation, the channel is first decomposed into sub-channels with different angle of departure. By exploiting the property of near line of sight (LoS) and location information, Kalman filtering is used to track the channel by predicting and modifying the channel gain of the LoS sub-channel. To further improve the tracking performance, a location-based sequentially optimal beam pattern design is proposed. Since placing pilot beams for many receive antennas with different locations in time or frequency division manner costs much system resource, the authors further propose a low-complexity grouping algorithm based on location. Finally, two transmission designs based on the proposed channel tracking scheme and the location only, respectively, are introduced. Simulations validate the efficiency of the authors' proposed tracking scheme and the corresponding transmission design, which shows the importance of location information and channel tracking in massive MIMO HST-WCS.

关键词： MIMO communication railway communication channel estimation Kalman filters receiving antennas antenna arrays location-aided channel tracking downlink transmission HST massive MIMO systems massive multiple-input multiple-output systems high-speed train wireless communication systems time-varying property channel estimation nonlinear channel variation departure angle near-line-of-sight location information Kalman filtering channel gain LoS subchannel location-based sequentially optimal beam pattern design receive antennas frequency division time division low-complexity grouping algorithm transmission design massive MIMO HST-WCS

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Pilot contamination reduction in TDD-based massive MIMO systems

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IET COMMUNICATIONS 2019年第10期13卷 1425-1432页

作者： Zhao, Junhui Ni, Shanjin Gong, Yi Zhang, Qingmiao Beijing Jiaotong Univ Sch Elect & Informat Engn 3 Shangyuancun Beijing Peoples R China East China Jiaotong Univ Sch Informat Engn Nanchang Jiangxi Peoples R China Southern Univ Sci & Technol Dept Elect & Elect Engn 1088 Xueyuan Rd Shenzhen Peoples R China

Channel estimation in time division duplexing (TDD)-based massive multiple-input multiple-output (MIMO) systems is heavily hampered by the pilot contamination, which constitutes a major bottleneck on the overall system performance. This study considers the pilot contamination problem in multi-cell TDD-based massive MIMO systems, and analytical expressions are presented on the normalised mean square error (NMSE) of the minimum mean square error channel estimation algorithm. Based on the obtained NMSE, this study proposes an optimal pilot assignment strategy to minimise the effect of pilot contamination. In order to further improve the system performance, a pilot design-based channel estimation scheme is proposed, where Chu sequences with perfect auto-correlation property are employed to design the optimal pilot sequences aiming at acquiring the accurate channel state information. Simulation results show that the proposed pilot assignment strategy outperforms the random pilot assignment method, and approaches to the performance of the exhaustive search method which requires high computational complexity. Moreover, the performance gain of the pilot design-based channel estimation scheme is verified in massive MIMO systems.

关键词： channel estimation time division multiplexing MIMO communication computational complexity least mean squares methods pilot design-based channel estimation scheme pilot contamination reduction pilot contamination problem multicell TDD-based massive MIMO systems normalised mean square error optimal pilot assignment strategy optimal pilot sequences accurate channel state information random pilot assignment method time division duplexing massive multiple-input multiple-output systems minimum square error channel estimation algorithm Chu sequences perfect auto-correlation property exhaustive search method computational complexity

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