Massive MIMO Propagation Modeling With User-Induced Coupling Effects Using Ray-Tracing and FDTD
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The article describes a numerical approach for Massive MIMO channel modeling that accounts for the effects of electromagnetic coupling between a user and the receiving device. The modeling is performed by a combination of the Finite-Difference Time-Domain and the Ray-Tracing methods, supplemented with a stochastic geometry model of the propagation environment. The influence of user-coupling on the channel properties was studied statistically using the singular value spread and matrix power ratio metrics of the channel correlation matrix. The time-averaged Poynting vector distribution in the near-field of the receiver was evaluated using a realistic human phantom model and the Maximum Ratio Transmission precoding scheme in the downlink. The average enhancement of the time-average Poynting vector magnitude at the receiver location, compared to the surrounding area, was found to be around 10 dB when using 36 antenna elements at the base station. The electromagnetic field exposure of the phantom was assessed in terms of the 10g-average peak-spatial Specific Absorption Rate and compared with the existing public guidelines. Comparison of the EMF and exposure results provides a new perspective on the future regulatory procedures.Keywords:
Spatial correlation
Spatial multiplexing have drawn a lot of attention for many years due to their great potential to achieve high throughput of MIMO systems implemented in wireless communication systems. It is well known that in a single user case the capacity scales linearly with the minimum number of transmit and receive antennas. Many linear precoding techniques require each antenna to transmit its own data. In this paper, we analyze the latest technology of MIMO with theoretic background. We compare the increasing features of capacity by using two precoding methods based on spatial multiplexed system. We apply two precodings to multiple antennas, considering MU-MIMO downlink. Finally, the simulation result demonstrates how the number of antennas has an effect on capacity.
Spatial multiplexing
Spatial correlation
Zero-forcing precoding
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Channel state information(CSI) affects the performance of Tomlinson-Harashima precoding(THP).For actual time-varying multi-input multi-output(MIMO) channels,there is imperfect CSI at both ends due to estimation errors at the receiver and estimation errors,feedback delay at the transmitter.A THP design over transmitter and receiver spatial correlation is proposed,which uses zero-forcing(ZF) THP criteria and combines with Bayes' estimation theorem.Simulation results show that the proposed THP can effectively decrease the unfavorable influence caused by spatial correlation,channel estimation errors,feedback delay and time variations,and has better bit error rate(BER) performance.
Spatial correlation
Channel state information
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Spatial correlation among received signals has a significant impact on the performance of a multiple- input multiple-output (MIMO) system. In prior research, expressions were derived for the spatial correlation between the signals received at a uniform linear array (ULA) by assuming that the propagation environment has a single cluster, low angular spread or that the received rays arrive only along the broadside of the array. In this paper, analytical expressions are derived for the spatial correlation between the received signals of a ULA and uniform circular array without making any of the above mentioned assumptions. The derivation can be extended to suit most planar antenna array configurations. This makes the derived expressions valid for most practical propagation channels. Finally, we show using simulations that the derived expression evaluates spatial correlation more accurately than the existing models.
Spatial correlation
Planar array
Circular buffer
Array gain
Expression (computer science)
Broadside
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We present a precoding approach for spatial modulation (SM) for increased robustness against spatial correlations over slow fading Rayleigh channels. This approach, based on phase-rotation of the transmitted symbol according to the active transmit antenna, can be implemented without changing the power budget or needing any explicit knowledge of the channel state information at the transmitter. The optimum precoding coefficients are determined so as to minimize the asymptotic average bit-error rate. Both theoretical analysis and simulation results indicate significant performance improvements even in the case of heavily correlated transmit antennas.
Spatial correlation
Robustness
Zero-forcing precoding
Channel state information
Spatial modulation
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It has been shown recently that dirty paper coding (DPC) achieves optimum sum-rate capacity in a multi-antenna broadcast channel with full channel state (CSI) information at the transmitter. With only partial feedback, random beamforming (RBF) is able to match the sumrate of DPC for large number of users. However, in the presence of spatial correlation, RBF incurs an SNR hit as compared to DPC. In this letter, we explore precoding techniques to reduce the effect of correlation on RBF. We thus derive the optimum precoding matrix that minimizes the rate gap between DPC and RBF. Given the numerical complexity involved in calculating the optimum precoder, we derive approximate precoding matrices that are simple to calculate and close in performance to the optimum precoder.
Spatial correlation
Zero-forcing precoding
Channel state information
Dirty paper coding
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In this paper we study the data-error performance of Linear Dispersion (LD) codes under spatial correlated multiple-input multiple-output (MIMO) channels. We propose a new precoding algorithm for LD codes by minimizing the pairwise error probability (PEP). This precoding can totally remove the spatial correlation existing in the transmitter. Particularly, the precoding process can be integrated into the LD codes design process, which means that there is no extra computation required in the coding process.
Spatial correlation
Pairwise error probability
Zero-forcing precoding
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In order to exploit multiuser diversity gain and spatial multiplexing gain for multi-user MIMO system with spatial correlation Ricean fading channel, a joint multi-user precoding and scheduling algorithm is proposed based on partial channel state information (CSI). Utilizing partial instantaneous CSI and statistical CSI for all users, the base station (BS) estimates the channel for each user using constrained maximum likelihood (CML) approach, and then schedules a group of users with optimal precoding using the estimated channels. Simulation results demonstrate that the proposed scheme greatly improves system throughput with a bit of feedback overhead.
Channel state information
Spatial correlation
Spatial multiplexing
Zero-forcing precoding
Diversity gain
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A Gauss-Seidel approach to precoding design for joint transmission of distributed correlated sources
We consider the problem of transmitting multiple spatially distributed correlated sources to a common destination (e.g. a fusion center or an access point) in wireless sensor networks (WSNs). The correlated data from multiple sensors are jointly transmitted to the destination via orthogonal channels. We assume that the channel between each sensor and the receiver is multiple-input multiple-output (MIMO), with each sensor and the receiver equipped with multiple transmit/receive antennas. In this framework, we study the problem of joint design of linear precoders for all sensors by assuming the knowledge of the instantaneous channel state information (CSI), with the objective of maximizing the mutual information between the sources and the destination. We propose a Gauss-Seidel iterative approach which successively optimizes the precoding matrix associated with each sensor, while fixing the other precoding matrices. Numerical results show that the proposed algorithm that takes into account the spatial correlations across sensors can achieve higher capacity than conventional methods that neglect the spatial correlations.
Spatial correlation
Channel state information
Zero-forcing precoding
Fusion center
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최근 해상 통신망에서 대용량 데이터 전송이 요구 되고 있다. 이에 따라 본 논문에서 다중 입출력의 공간 다중화 기법을 고려하였다. 하지만 공간 다중화 기법은 송 수신 안테나 사이의 공간 채널 상관 및 직접파 성분에 의해 수신 성능이 열화 된다. 특히, 해상 통신 환경에서 송 수신기 주변의 산란체가 거의 존재하지 않아 채널 상관 및 직접파 수신이 빈번하게 발생한다. 이를 위해 수신기로부터 채널정보를 피드백 받아 프리코딩을 적용하여 수신 성능 열화를 줄일 수 있다. 하지만 채널 상관과 직접파 성분이 동시에 존재 하는 경우 공간 다중화를 위한 프리코딩은 폐형 수식 도출 및 적용의 어려움이 있다. 따라서 본 논문에서는 수신기로부터 채널정보를 요구하지 않는 개루프 프리코딩 기반으로 채널 상관 및 LOS에 대한 성능을 분석하여 해상 통신망 환경에서 고속 데이터 전송 방법을 제시하였다. 개루프 프리코딩을 적용한 공간 다중화 기법은 수신기로부터 채널 정보를 피드백 받지 않고 채널 상관 및 직접파 수신 환경에서도 성능 열화를 줄일 수 있음을 확인하였다. 따라서 해상 통신 환경에서 신뢰성 및 고속 데이터 전송을 위한 기법으로 개루프 프리코딩 기반의 공간 다중화 기법이 적합할 것으로 예상된다. Recently, high data rate transmission is required in maritime communication. In this paper, we consider multiple input multiple output (MIMO) spatial multiplexing (SM). However, the performance of SM is severly degraded due to spatial channel correlation and line-of-sight (LOS) component. In the maritime communication, the MIMO channel correlation and LOS are critical due to the lack of scatteres around the transmitter and/or the receiver. When the feedback of channel information is available, precoding can enhance the error performance by exploiting the channel information. However, it is difficult to derive closed-form solution considering both the correlation and LOS. In this paper, we present open-loop precoding-based spatial multiplexing transmission method by showing that the effect of performance for the correlation and LOS. It is shown that the open-loop precoding can mitigate the performance degradation due to the LOS as well as the correlation. Consequently, we expect that the proposed open-loop precoding can be adopted to the maritime communication system.
Spatial multiplexing
Spatial correlation
Zero-forcing precoding
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This paper addresses the critical problem of high overhead in channel information acquisition for hybrid precoding in massive multiple-input multiple-output (MIMO) system. With the employment of large-scale massive antennas in the next generation 5G wireless system, the high overhead in the estimation of channel state information (CSI) for the precoding has been regarded as one of the main challenges that prevent its implementations. On the other hand, other efficient hybrid precoding schemes such as beam sweeping based two stage precoding have limited performance compared with the complete CSI based precoding algorithm. This paper proposes a novel technique to quickly acquire the channel spatial correlation of the large number of antennas, which can be used for hybrid precoding design. This technique can greatly reduce the training overhead while maintain the capability of generating highly user-specific analog beamforming. The simulation results show that the proposed technique can achieve similar performance with the traditional complete CSI based precoding but only require even less reference signal (RS) symbols than the beam sweeping scheme.
Spatial correlation
Zero-forcing precoding
Channel state information
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