Showing papers on "Zero-forcing precoding published in 2020"

Local Partial Zero-Forcing Precoding for Cell-Free Massive MIMO

Abstract: Cell-free Massive MIMO (multiple-input multiple-output) is a promising distributed network architecture for 5G-and-beyond systems. It guarantees ubiquitous coverage at high spectral efficiency (SE) by leveraging signal co-processing at multiple access points (APs), aggressive spatial user multiplexing and extraordinary macro-diversity gain. In this study, we propose two distributed precoding schemes, referred to as local partial zero-forcing (PZF) and local protective partial zero-forcing (PPZF), that further improve the spectral efficiency by providing an adaptable trade-off between interference cancelation and boosting of the desired signal, with no additional front-hauling overhead, and implementable by APs with very few antennas. We derive closed-form expressions for the achievable SE under the assumption of independent Rayleigh fading channel, channel estimation error and pilot contamination. PZF and PPZF can substantially outperform maximum ratio transmission and zero-forcing, and their performance is comparable to that achieved by regularized zero-forcing (RZF), which is a benchmark in the downlink. Importantly, these closed-form expressions can be employed to devise optimal (long-term) power control strategies that are also suitable for RZF, whose closed-form expression for the SE is not available.

Fast matrix inversion methods based on Chebyshev and Newton iterations for zero forcing precoding in massive MIMO systems

Abstract: In massive MIMO (mMIMO) systems, large matrix inversion is a challenging problem due to the huge volume of users and antennas. Neumann series (NS) and successive over relaxation (SOR) are two typical methods that solve such a problem in linear precoding. NS expands the inverse of a matrix into a series of matrix vector multiplications, while SOR deals with the same problem as a system of linear equations and iteratively solves it. However, the required complexities for both methods are still high. In this paper, four new joint methods are presented to achieve faster convergence and lower complexity in matrix inversion to determine linear precoding weights for mMIMO systems, where both Chebyshev iteration (ChebI) and Newton iteration (NI) are investigated separately to speed up the convergence of NS and SOR. Firstly, joint Chebyshev and NS method (ChebI-NS) is proposed not only to accelerate the convergence in NS but also to achieve more accurate inversion. Secondly, new SOR-based approximate matrix inversion (SOR-AMI) is proposed to achieve a direct simplified matrix inversion with similar convergence characteristics to the conventional SOR. Finally, two improved SOR-AMI methods, NI-SOR-AMI and ChebI-SOR-AMI, are investigated for further convergence acceleration, where NI and ChebI approaches are combined with the SOR-AMI, respectively. These four proposed inversion methods provide near optimal bit error rate (BER) performance of zero forcing (ZF) case under uncorrelated and correlated mMIMO channel conditions. Simulation results verify that the proposed ChebI-NS has the highest convergence rate compared to the conventional NS with similar complexity. Similarly, ChebI-SOR-AMI and NI-SOR-AMI achieve faster convergence than the conventional SOR method. The order of the proposed methods according to the convergence speed are ChebI-SOR-AMI, NI-SOR-AMI, SOR-AMI, then ChebI-NS, respectively. ChebI-NS has a low convergence because NS has lower convergence than SOR. Although ChebI-SOR-AMI has the fastest convergence rate, NI-SOR-AMI is preferable than ChebI-SOR-AMI due to its lower complexity and close inversion result.

Multi-Satellite Multi-User MIMO Precoding: Testbed and Field Trial

Abstract: Precoding for multibeam satellite systems with full frequency reuse in a multi-user multiple-input multiple-output (MU-MIMO) downlink scenario is addressed. A testbed is developed to perform an over-the-air field trial of zero forcing precoding for the spatial multiplexing of two separate video streams over two co-located geostationary satellites. Commercial-off-the-shelf DVB-S2x receivers in two single-antenna user terminals (UTs) are operated to successfully decode two independent video streams. To this end, particular attention is paid to a comprehensive assessment of the practical synchronization tasks of a precoding based MU-MIMO system. In particular, carrier frequency recovery and carrier phase synchronization in the most challenging multi-satellite scenario with different oscillators in the payloads is performed. An estimation method for channel state information (CSI), i.e. the complex channel coefficients, is also proposed and implemented. The successful video transmission finally constitutes the first field trial of MU-MIMO precoding and proves the feasibility of precoding concepts for multibeam satellite systems.

Multi-Satellite Multi-User MIMO Precoding: Testbed and Field Trial

Abstract: Precoding for multibeam satellite systems with full frequency reuse in a multi-user multiple-input multiple-output (MU-MIMO) downlink scenario is addressed. A testbed is developed to perform an over-the-air field trial of zero forcing precoding for the spatial multiplexing of two separate video streams over two co-located geostationary satellites. Commercialoff-the-shelf DVB-S2x receivers in two single-antenna user terminals (UTs) are operated to successfully decode two independent video streams. To this end, particular attention is paid to a comprehensive assessment of the practical synchronization tasks of a precoding based MU-MIMO system. In particular, carrier frequency recovery and carrier phase synchronization in the most challenging multi-satellite scenario with different oscillators in the payloads is performed. An estimation method for channel state information (CSI), i.e. the complex channel coefficients, is also proposed and implemented. The successful video transmission finally constitutes the first field trial of MUMIMO precoding and proves the feasibility of precoding concepts for multibeam satellite systems.

Large System Analysis of Downlink MISO-NOMA System via Regularized Zero-Forcing Precoding With Imperfect CSIT

Abstract: This letter studies the multiple-input single-output (MISO) non-orthogonal multiple-access (NOMA) downlink using regularized zero-forcing (RZF) precoding with imperfect channel state information (CSI). We first propose a new user scheduling scheme based on imperfect CSI and a model to characterize the channel correlation between the weak and strong users. Then we derive an approximate expression of the ergodic sum-rate using large-system random matrix theory. This approximation permits us to derive the optimal power allocation scheme that satisfies the rate requirement of the weak users. Simulation results are presented to confirm the accuracy of the approximation and reveal the relationships between the ergodic sum-rate, the channel correlation, and other system parameters.

Outage Analysis for MISO Zero-Forcing Precoding With Outdated CSI

Abstract: Zero-forcing precoding is a commonly-used multiple-user, multiple-input multiple-output beamforming technique. Applying such precoding, the signal-to-interference-plus-noise ratio (SINR) statistics with outdated channel state information, which involve various projections related to the multi-dimensional channel vectors and precoding vectors, have never been explicitly derived. In this paper, for the multiple-input single-output scenario with uniform power allocation, the distributions of these projections are derived, and then the SINR distribution and the conditional outage probability can be computed using those distributions.

PCA-Aided Linear Precoding in Massive MIMO Systems with Imperfect CSI

Abstract: In this paper, a low-complexity linear precoding algorithm based on the principal component analysis technique in combination with the conventional linear precoders, called Principal Component Analysis Linear Precoder (PCA-LP), is proposed for massive MIMO systems. The proposed precoder consists of two components: the first one minimizes the interferences among neighboring users and the second one improves the system performance by utilizing the Principal Component Analysis (PCA) technique. Numerical and simulation results show that the proposed precoder has remarkably lower computational complexity than its low-complexity lattice reduction-aided regularized block diagonalization using zero forcing precoding (LC-RBD-LR-ZF) and lower computational complexity than the PCA-aided Minimum Mean Square Error combination with Block Diagonalization (PCA-MMSE-BD) counterparts while its bit error rate (BER) performance is comparable to those of the LC-RBD-LR-ZF and PCA-MMSE-BD ones.

Achievable Rate of Multi-Cell Downlink Massive MIMO Systems with D2D Underly

Abstract: In this paper, a new analytical framework model based on stochastic geometry for Device-To-Device (D2D) communication underlaying multi-cell massive Multi-Input-Multi-Output (MIMO) system is proposed. Assuming Maximum Ratio Transmission or Zero Forcing precoding scheme for cellular downlink transmission, the impact of RF mismatches and achievable rate of cellular user are analytically derived. The studied model assumes truncated Gaussian distribution to model RF mismatches, D2D interference, inter cell interference, and intra-cell interference. Accordingly, closed form expressions of lower-bound achievable data rate for cellular users is derived. Moreover, asymptotic performance analysis under the assumption of large number of antennas has been performed. Simulation results are found to coinside with the theoritical results and validated our model.

Centralized Single FPGA Real Time Zero Forcing Massive MIMO 5G Basestation Hardware and Gateware

Abstract: In the following a massive MIMO 5G < 6 GHz base station implementation is presented which is capable of realtime zero forcing precoding on a single central signal processing (CSP) FPGA. The built prototype is capable of simultaneously driving M = 196 separate RF ports all delivering samples to the CSP FPGA. Each RF chain’s ADCs and DACs are running at 40 MSPS at full roll-out. The power consumption of the remote radio head is 1.56 W per RF port when running at a sample rate of 15.36 MSPS. The system allows for hardware-in-the-loop operation and real-time baseband signal processing with a round trip delay of 278 μs when processing 64 antennas and 8 simultaneous user streams for an 5GNR-like OFDMA system with 1024 sub-carriers and 50 resource blocks (600 used subcarriers) with a sample frequency of 15.36 MHz and a central signal processing clock of 184.32 MHz. The reciprocity calibration system runs completely internal to the system and doesn’t radiate signals for the calibration procedure. Furthermore the central single-FPGA signal processing architecture allows for simplified implementation of algorithms and maintenance of the system.

Downlink user selection for massive-MIMO-OFDM systems using ZF precoding

Abstract: By the use of a large number of M antennas in the base station side, makes it possible to beamform different signals to different users, so the signals add up constructively at the desired user and destructively everywhere else, that is why massive Mimo-ODFM combing with beamforming is a promising technology for next generation wireless communication network (5G). Indeed, the performance of Massive MIMO systems is systematically dependent on users' selection method especially when the number of users is huge in the cell. In this paper, we focus on the performance of such a system in terms of max rate using zero forcing precoding method.

Secrecy Rate Maximization in Millimeter Wave SWIPT Systems based on Non-Linear Energy Harvesting

Abstract: In this paper, we study the secrecy rate maximization in millimeter-wave simultaneous wireless information and power transfer systems, where two radio frequency chain antenna architectures are considered. Then, a joint optimization problem of digital precoding vector, power splitting ratio and artificial noise covariance matrix is proposed, while non-linear energy harvesting and maximum transmit power constraint are considered. It is difficult to solve directly due to coupled variables and non-convexity, so we propose an alternating optimization algorithm based on semi-definite relaxation to solve it suboptimally. Meanwhile, an alternating optimization algorithm based on zero forcing precoding is proposed to reduce the complexity. Finally, simulation results prove the validity of the proposed different algorithms.