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Correlation exists in all practical channels, and each channel's correlation level varies. Determining correlation matrices while estimating the channel and precoding is vital in providing spatial directivity to the signals. This paper considers the performance analysis of the downlink multi-cell multiuser Massive Multiple Input Multiple Output (mMIMO) system with user-specific correlation matrices for the Rician Fading channel. Using the Random Matrix Theory (RMT) results, the closed-form for the asymptotic analysis of ergodic downlink rate per user terminal (UT) is derived for the spatially correlated system with Regularized Zero-Forcing (RZF) scheme. A realistic multipath environment consisting of a dominant line-of-sight (LOS) path along the non-deterministic non-line-of-sight (NLOS) component with imperfect channel information and pilot contamination is considered for deriving the expression. The system is evaluated for the carrier frequency of 30 G H z in the mmWave range with different parameters using Monte Carlo simulations to validate the derived expression. The numerical results show that the derived expression for ergodic user rate provides a tight approximation for the large-dimensional system and accurate results for small values. As for the Rician Factor, κ = 0.5 , transmit power of 10 d B and training power of 6 d B , the average user rate obtained for M = 100 and K = 50 is 1.1233 bits/sec/Hz/User/cell for simulated value and 1.1243 bits/sec/Hz/User/cell for theoretical value. The proposed correlated multicellular mMIMO system is shifted from the mmWave range to s u b - 6 G H z to compare it with the existing system in (Sanguinetti et al. in IEEE Transactions on Communications 67:1939–1955, 2018). The derived results show the improvement in system throughput for the proposed system. [ABSTRACT FROM AUTHOR]

This research examines the performing of linear precoding techniques in downlink massive MIMO systems. The downlink massive MIMO systems, linear precoding techniques as combined to zero forcing (ZF) and matched filter (MF), truncated polynomial expansion (TPE) and regularized zero forcing (RZF). The output of massive MIMO downlinks is analyzed with linear precoding. The performing of sum rate precoding of signal-to-noise (SNR) ratio, as well as numerous transmitter-receiver antennas, is discussed, including defective CSI and inter-user interference. On the channel, the transmitter as entire state information. The data describes how a signal travels from the transmitter to the receiver, taking into account factors like as space scattering and power decay. They appearance that given a perfect chain, the performing analyzed of two linear precoding approaches, namely Zero Forcing (ZF) and Matched filter (MF) for downlink mMIMO. The results demonstrate ZF, higher BER and sum rate as comparing to MF schemes, as well as a comparison of RZF and TPE average achievable rates. In multi-user scenarios, Kalman-based hybrid precoding (analog/digital) as used in a downlink throughput of 5.14 Gbps and a uplink rate of 2.26 Gbps. The impact of beam steering capability on both base stations (BS) and 5G user equipment (UEs) is also investigated. Based on the simulation results, the suggested approach provides a significant increase in spectral efficiency of 10.53 bps/Hz with 10 channel routes. [ABSTRACT FROM AUTHOR]

Cell-free large-scale multi-user MIMO is a promising technology for the 5G-and-beyond mobile communication networks. Scalable signal processing is the key challenge in achieving the benefits of cell-free systems. This study examines a distributed approach for cell-free deployment with user-centric configuration and finite fronthaul capacity. Moreover, the impact of scaling the pilot length, the number of access points (APs), and the number of antennas per AP on the achievable average spectral efficiency are investigated. Using the dynamic cooperative clustering (DCC) technique and large-scale fading decoding process, we derive an approximation of the signal-to-interference-plus-noise ratio in the criteria of two local combining schemes: Local-Partial Regularized Zero Forcing (RZF) and Local Maximum Ratio (MR). The results indicate that distributed approaches in the cell-free system have the advantage of decreasing the fronthaul signaling and the computing complexity. The results also show that the Local-Partial RZF provides the highest average spectral efficiency among all the distributed combining schemes because the computational complexity of the Local-Partial RZF is independent of the UTs. Therefore, it does not grow as the number of user terminals (UTs) increases. [ABSTRACT FROM AUTHOR]

In this paper, linear precoding (LP) algorithm has been studied to improve the bit error rate (BER) performance of large scale multiple input multiple output (MIMO) system. A new technique of enhancing the BER performance of linear precoding algorithm without complexity in hardware and mathematical calculations is proposed and it is used on a traditional LP algorithms like a Maximum Ratio Transmission (MRT), a Zero-Forcing (ZF), a Regularized Zero-Forcing (RZF), and a Minimum Mean Square Error (MMSE) for Millimeter wave MU-MIMO communication system. A new technique is also used to mitigate the BER gab problem between (ZF, MMSE) and (RZF, MMSE) linear precoding algorithms. The result shows that with using the new technique, the BER performance of modified LP significantly outperform their traditional LP by 10−5 when using 4 element of BS antenna, 10−6 when using 16 element of BS antenna and mitigate the BER gab problem at different signal to noise ratio (SNR). [ABSTRACT FROM AUTHOR]

Linear precoding algorithms with low complexity in massive multi-in multi-out system have always been a hot research topic to solve the problem of inter-cell interference. In this paper, we proposed a conjugate gradient-based regularized zero-forcing (CG-RZF) precoding algorithm, with which the base station can directly obtain the transmitted signal after RZF precoding and avoid directly solving the inverse matrix in RZF. Moreover, an RZF precoding algorithm based on a parallel conjugate gradient (Parallel-CGRZF) is also proposed, which can optimize initial values and iterative process of the aforementioned CG-RZF precoding algorithm. The simulation results have shown that the proposed CG-RZF and the optimized Parallel-CG-RZF precoding algorithm can significantly improve the performance of bit error rate with fast convergence speed compared with other precoding algorithms and can reduce the number of global communications. Meanwhile, the calculation complexity of the proposed CG-RZF and Parallel-CG-RZF precoding algorithm is much lower than the optimized Chebyshev iteration algorithm.

Massive MIMO systems (also known as 'large-scale antenna system' and 'full-dimension MIMO') significantly reduce air interface latency by using a large excess of service antennas over active terminals and time-division duplex operation. We consider the downlink of a time-division duplexing multicell multiuser MIMO system in which the base transceiver stations are equipped with a very large number of antennas. Assuming channel estimation through uplink pilots, arbitrary antenna correlations, and user distributions, we derive approximations of achievable rates with linear precoding techniques-namely, zero forcing, matched filtering, eigen-beamforming (EBF), and regularized zero-forcing (RZF). The approximations are tight in the large system limit with an infinitely large number of antennas and user terminals, but they match our simulations for realistic system dimensions. We further show that a simple EBF precoding scheme can achieve the same performance as RZF with one order of magnitude fewer antennas in both uncorrelated and correlated fading channels. Our simulation results show that our proposed precoding scheme is better than the conventional scheme. Moreover, we have used two channel environments for further analysis of our algorithm-long-term evolution advanced and millimeter wave mobile broadband channels. [ABSTRACT FROM AUTHOR]

Massive multiple-input-multiple-output (MIMO), also known as very-large MIMO systems, is an attracting technique in 5G and can provide higher rates and power efficiency than 4G. Linear-precoding schemes are able to achieve the near optimal performance, and thus are more attractive than non-linear precoding schemes. However, conventional linear precoding schemes in massive MIMO systems, such as regularized zero-forcing (RZF) precoding, have near-optimal performance but suffer from high computational complexity due to the required matrix inversion of large size. To solve this problem, we utilize the Cholesky-decomposition and Sherman-Morrison lemma and propose CSM (Cholesky and Sherman-Morrison strategy)-based precoding scheme to the matrix inversion by exploiting the asymptotically orthogonal channel property in massive MIMO systems. Results are evaluated numerically in terms of bit-error-rate (BER)and average sum rate. Comparing with the Neumann series approximation of inversing matrix, it is concluded that, with fewer operations, the performance of CSM-based precoding is better than conventional methods in massive MIMO configurations. [ABSTRACT FROM AUTHOR]

In this paper, the downlink signal-to-interference-plus-noise ratio (SINR) performance in multiuser large scale antenna systems with matched filter (MF) and regularized zero-forcing (RZF) precoding is investigated. The probability density function (PDF) for MF is derived and the distribution in high signal-to-noise ratio (SNR) regime is studied. Results indicate that the PDF of downlink SINR for MF converges to $$\mathcal F$$ distribution when the interference is dominant over noise. For MF, the asymptotic SINR is just the reciprocal of the ratio of the number of users $$U$$ to the number of transmit antennas $$N$$ , and is irrelevant to the average transmit power when $$N$$ and $$U$$ grow with fixed ratio. However, when $$U$$ is a large constant, the transmit power could be proportional to $$\ln N \big /N $$ to maintain a specified quality of service, as a result of the large scale antenna system effect. In addition, the closed form of asymptotic SINR for RZF is derived by solving two mathematical expectations related to eigenvalues of large dimensional random matrices. Simulation results validate the derived PDF and analytical results. [ABSTRACT FROM AUTHOR]

Modern wireless communications require an efficient spectrum usage and high channel capacity and throughput. Multiple-input and multiple-output (MIMO), Linear equalizers, multi-user detection and multicarrier code-division multiple access (MC-CDMA) are possible solutions to achieve spectral efficiency, high channel capacity, eliminate multiple access interference (MAI), eliminate Inter symbol interference (ISI) and robustness against frequency selective fading. In this paper, we combine all these techniques and investigate BER performance. We propose a low complexity receiver structure for Single-input Multiple-output (SIMO) downlink MC-CDMA systems. It employs an interference cancellation scheme to suppress the interference caused by the multipath fading channel. Also, the proposed scheme is developed for MIMO MC-CDMA system. The performance analysis of Downlink MIMO MC-CDMA systems with V-BLAST over frequency selective fading channel is investigated under various number of transmit and receive antennas. The simulation results show proposed SIMO equalization with parallel interference cancellation scheme is effective in reducing the ISI and the MAI. It improves the performance significantly and the simulation results show that MIMO MC-CDMA with V-BLAST multi-user detection provides high data rate and the BER significant improvement. [ABSTRACT FROM AUTHOR]