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In order to maximize the available data rate and spectrum utilization efficiency, a high-throughput satellite communication system adopts the full spectrum reuse scheme, which will cause serious co-frequency interference. In this paper, a forward link model, considering the effects of free space loss, rainfall attenuation, and beam gain, is established, and the classical low-complexity of the zero-forcing precoding algorithm is improved in order to solve the serious co-frequency interference. Moreover, the regularized zero-forcing precoding algorithm considering the influence of system noise is studied, and a low complexity regularized zero-forcing dirty paper precoding algorithm is proposed, whose basic principle is to sort users based on the principle of channel maximum norm selection and practical application scenarios. Simulation results show that it can encode users sequentially, according to the channel conditions, to maximize the SINR (signal-to-interference-plus-noise ratio) and increase the throughput of the system.

In this paper, we have proposed user grouping method and new user selection techniques in TDD Massive (MIMO) systems. Using K-means clustering algorithm we separate the users into different groups. Upon user groups are formed users are selected from different groups with Semi-Orthogonal (SO) and random user selection criteria. We use two user selection method to select users from different groups, those are-(i) Users are selected in intra-group those are SO with each other along with it also SO with other group’s users, (ii)-Users are selected from inter-group those are SO with each other. For antenna scheduling we used maximum channel gain measure in both the user selection situation. Semi-Orthogonal user selection (SOU) and antenna scheduling with zero forcing precoding demonstrated maximum system sum-rate that is seen in results. In table-1 appraised the computational cost of our modified SOU algorithm. The proposed algorithm’s efficiency is explored through the simulations.

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtained. In order to achieve the aforementioned objectives, this paper presents a feasible DL training sequence design based on a partial CSI estimation approach for an FDD massive-MIMO system with a shorter coherence time. To this end, a threshold-based approach is proposed for a suitable DL pilot selection by exploring the statistical information of the channel covariance matrix. The mean square error of the proposed design is derived, and the achievable sum rate and bit-error-rate for maximum ratio transmitter and regularized zero forcing precoding is investigated over different BTS topologies with uniform linear array and uniform rectangular array. The results show that a feasible performance in the DL FDD massive-MIMO systems can be achieved even when a large number of antenna elements are deployed by the BTS and a shorter coherence time is considered.

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.

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.

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 \textit{local partial zero-forcing} (PZF) and \textit{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., This paper was accepted for publication in IEEE Transactions on Wireless Communications on March 31, 2020. {\copyright} 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses

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.

In this letter, the impact of two variants of zero-forcing (ZF) precoding (conventional and minimax) on the performance of massive multiple-input–multiple-output (MIMO) transmitters is investigated through simulations and experiments. In massive MIMO transmitters, the average-power levels across the radio frequency (RF) chains depend on the choice of precoder and the channel conditions. Compared to the conventional ZF precoder, the minimax variant results in significantly less variations in the average-power levels across the RF chains and, consequently, in less disparity between their operating characteristics. Thus, the minimax precoder, albeit requiring more computational resources, reduces the variation of the transmitter’s performance with the channel conditions. Experiments performed using the two ZF variants, in conjunction with digital predistortion, on a two-user four-chain MIMO transmitter under 200 different channel realizations revealed that the minimax variant allows for up to 10 dB and 8% reductions in the adjacent-channel power ratio and root normalized mean-square error, respectively, in each chain.

Fully digital precoding has superior performance for millimeter wave (mmWave) multiple input and multiple output (MIMO) system. In fully digital precoding, each antenna is connected to one RF chain which results in high hardware complexity and high cost. Non-orthogonal multiple access (NOMA) is one of the promising techniques in future mobile communication. In this paper, we propose a fully digital mmWave massive MIMO system with a reduced hardware complexity and reduced energy consumption. The proposed system reduces the number of antennas and consequently the number of RF chains by applying a three stages antenna reduction algorithm. Moreover, a clustering algorithm is proposed in which users within same group are highly correlated, and users in different groups have low correlation with each other. The performance of the proposed system is evaluated in terms of energy efficiency and spectral efficiency. Numerical results show that the proposed system has superior performance in terms of energy efficiency at the expense of slight decrease in spectral efficiency.

In this work, we investigate the impact of two cooperative unmanned aerial vehicle (UAV)-based jammers on the secrecy performance of a ground wireless network in the presence of an eavesdropper. For that purpose, we investigate the secrecy-area related metrics, Jamming Coverage and Jamming Efficiency. Moreover, we propose a hybrid metric, the so-called Weighted Secrecy Coverage (WSC) and a virtual distributed multiple-input-multiple-output (MIMO)-based zero-forcing precoding scheme to avoid the jamming effects on the legitimate receiver. For evaluating these metrics, we derive a closed-form position-based metric, the secrecy improvement. Our mathematical derivations and comparative simulations show that the proposed zero-forcing scheme leads to an improvement on the secrecy performance in terms of the WSC, and provides conditions for improvement of Jamming Efficiency. They also show positioning trends on the UAVs over a fixed orbit around the legitimate transmitter as well as power allocation trends for optimal secrecy.

In the context of cell-free massive multi-input multi-output (mMIMO), zero-forcing precoding (ZFP) requires the exchange of instantaneous channel state information and precoded data symbols via a fronthaul network. It causes considerable propagation and processing delays, which degrade performance. This letter analyzes the impact of channel aging on the performance of ZFP in cell-free mMIMO. The aging effects of not only user mobility but also phase noise are considered. Numerical results in terms of per-user spectral efficiency are illustrated.

This paper studies the low-SNR regime performance of a scalar complex K -user interference channel with Gaussian noise. The finite bandwidth case is considered, where the low-SNR regime is approached by letting the input power go to zero while bandwidth is small and fixed. We show that for all \delta>0 there exists a set with non-zero measure (probability) in which the wideband slope per user satisfies Slope, Comment: submitted to Information Theory, IEEE Transactions on

We analyze the downlink of a massive multiuser multiple input, multiple output (MIMO) system where antenna units at the base station are connected in a daisy chain without a central processing unit and only possess local channel knowledge. For this setup, we develop and analyze a linear precoding algorithm for suppressing interuser interference. It is demonstrated that the algorithm is close to zero-forcing precoding in terms of performance for a large number of antennas. Moreover, we show that with careful scheduling of processing across antennas, requirements for interconnection throughput are reduced compared with the fully centralized solution. Favorable tradeoff between performance and interconnection throughput makes the daisy chain a viable candidate topology for real-life implementations of base stations in MIMO systems where the number of antennas is very large.

This paper studies multi-user multi-cell visible light communications networks in which each cell is composed of multiple light emitting diode (LED) arrays. The use of multiple LED transmitters enables each cell to support multiple users by means of precoding techniques. In such multi-user multi-cell networks, the signal for each user can be severely interfered not only by the signals that are intended to other users in the same cell, i.e., intra-cell interference, but also by the signals for users of the other cells, i.e., inter-cell interference. While intra-cell interference can be handled by the underlying precoding scheme, it is hard to deal with the inter-cell one. This paper focuses on cell coordination/cooperation strategies and their corresponding coordinated/cooperative precoder designs as the approaches to alleviate, or possibly, to cancel out the inter-cell interference. We first derive lower and upper bounds on the capacity of Gaussian interference channels with amplitude constraints on the input and the interference. Capitalizing on derived bounds and the zero-forcing scheme as the underlying precoding technique, optimal coordinated/cooperative precoding designs to maximize users’ sum-rate are investigated under the non-negativity and amplitude-limited constraints on the channel inputs. The comprehensive numerical results are presented to compare the performance of the considered coordination/cooperation strategies.

Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer, but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combing and zero forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show substantial benefits in terms of energy usage can be achieved without sacrificing throughput, and that both signalling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling.

Recent developments in visible light communications (VLC) have focused on enhancing its security and privacy. This paper studies the physical layer security in VLC networks with multiple users when there is a single wiretap eavesdropper. In particular, our aim is to design the optimal artificial noise (AN)-aided precoding scheme to improve the secrecy performance in terms of legitimate users and eavesdropper’s signal-to-interference-plus-noise ratios (SINRs). The purpose of our AN-aided precoding design is to ensure a fairness of the legitimate users’ SINRs while impairing the quality of eavesdropper’s channel as much as possible. Depending on the availability of the eavesdropper’s channel state information (CSI) at the transmitters, there are generally two design strategies. When the eavesdropper’s CSI is unknown to the transmitters (i.e., passive eavesdropper), the AN is constructed to be orthogonal to the users’ aggregate channel matrix. In case the eavesdropper’s CSI is available (i.e., active eavesdropper), the AN design strategy is to keep the SINR of the eavesdropper below a certain predefined threshold. Aside from the general design, we also study a specific design with the zero-forcing (ZF) technique and compare its performance with that of the general design. In both designs, numerical results show that significant gaps between users’ and eavesdropper’s SINR can always be achieved, thus guaranteeing a high secrecy performance. It is also observed that while the general design outperforms the ZF one in terms of the users’ SINRs, it does not result in lower eavesdropper’s SINRs compared to the ZF design, especially in the low transmit power region.

In this paper, security issue in multiple input multiple output (MIMO) multicasting system has been analyzed in the presence of a group of eavesdroppers in cognitive radio networks (CRNs). Primary base station (PBS) and secondary base station (SBS) communicate with multiple primary and secondary receivers, respectively via a precoding relay having multiple antennas. At first, considering interference the secrecy multicast capacity at the primary receivers (PRs) and the secondary receivers (SRs) has been calculated and investigated the impact of interferences on it. Then, the zero-forcing (ZF) precoding technique at the relay has been employed which enhances the secrecy multicast capacity at the PRs and SRs by zeroing the impact of interference on each other. Secondly, the existing constructive interference energy of the communication medium employing selective precoding (SP) technique at the relay has been used to improve the secrecy multicast capacity of the PRs and SRs. Finally, phase alignment precoding (PAP) technique at the relay has been introduced which uses the destructive part of interference for further increase in the secrecy multicast capacity at the PRs and SRs. It is observed that among the three precoding techniques, the best performance is achieved by using the PAP at the relay in terms of secrecy multicast capacity and secure outage probability analysis. This is due to the fact that PAP technique at the relay not only uses the constructive interference part but also it rotates the destructive interference part in such a way that the resulting interference is always instantaneously constructive. So using these precoding relays interference power can be used to enhance system performance without increasing base station power.

We investigate the throughput of a multi-user multiple-input multiple-output aviation network where multiple aircraft are connected to a High Throughput Satellite (HTS). We assume full frequency reuse in the downlink and a multibeam antenna architecture with multiple reflectors on the HTS. To maximize the system throughput, we apply zero forcing precoding along with a scheduling algorithm to group multiple aircraft that are simultaneously served with data via space division multiple access. For a more realistic scenario, the flight paths of the airplanes are based on real airline routes, and interference from terrestrial fixed service stations is considered. Our simulation results show that the proposed concept enables a massive throughput increase while the required update rate of the precoder coefficients and the user groups remain moderate.

Comunicació presentada a: GLOBECOM 2020 celebrat del 17 a l'11 de desembre de 2020 a Taipei, Taiwan. This paper tackles the problem of zero-forcing (ZF) precoding for the downlink of centralized radio-access networks operating in a cell-free fashion. While the customary workhorse of ZF precoding is the channel pseudo-inverse, because of the separate power constraint at each participating access point, the pseudo-inverse is not optimum. Rather, it can be improved upon by other inverses that allow conveying stronger signals (or, equivalently, consuming less power) while respecting the same ZF conditions. Motivated by the enormous disparity in computational cost between simple pseudo-inversion and general inversion, we ascertain the performance disadvantage of the former in a wide range of conditions. The welcome conclusion is that pseudo-inversion is close-to-optimum for all operational regimes of interest. Work supported by the European Research Council under the H2020 Framework Programme/ERC grant 694974, and by MINECO's Projects RTI2018-102112 and RTI2018-101040.

Receive Spatial Modulation (RSM) uses the index of the receive antenna to convey additional information bits, which reduces the receiver complexity and improves spectral efficiency. Additionally, it provides inherent physical layer security using the Zero-forcing (ZF) precoding technique. However, the channel becomes vulnerable to eavesdropper (Eve) if the channel impulse response is assumed to be time-invariant or stationary through coherent block intervals. In this paper, a physical layer secure scheme is proposed based on phase index RSM to combat eaves-droppers that use k-nearest neighbors (KNN) supervised pattern recognition. The average bit error rate (BER) performance shows the ability of the proposed scheme to provide a suitable level of security while degrading the average BER performance of Eve.

We study the performance of linear zero-forcing (ZF) precoding in multiuser multiple-input single-output visible light communications (VLC) when we are able to select the receiving orientation angle (ROA) of each user. For radio-frequency communications, the non-line-of-sight rich scattering environment usually ensures the linear independence among user's channels. However, this condition is less likely to happen in VLC systems, degrading the performance of ZF precoding. In this work, we propose a variable ROA (vROA) photodetector able to modify its orientation vector in order to generate semi-orthogonal channel responses among users. We derive the algorithm for determining the orientation of the vROA photodetector of each user, obtaining optimal and suboptimal solutions with high and low complexity, respectively. Simulation results show that the performance of ZF precoding is improved considerably by managing the users ROA. This work has been supported by the Spanish National Project TERESAADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE) and the research project GEOVEOLUZ-CM-UC3M. Publicado

It is now well known that employing channel knowledge based on signaling techniques in wireless mobile ad-hoc networks (MANET) system can yield large improvements in almost all performance metric. Here we proposed the adaptive scheduling, in which the work done is based upon the bandwidth information of channel to provide better quality of service (‘QoS’) to the cell-edge mobile stations. Channel information is critical based on which scheduling is carried out. The bandwidth channel information contains estimation delay, the pilot channel noise and pilot contamination. Afterwards, Zero Forcing precoding methodology has applied for removing the interference at user nodes, destination nodes and gateway side. By extending the characteristics of ZF, the modified Zero Forcing (MZF) has proposed to achieve higher throughput rate and higher spectrum efficiency. The achievable-rates of the ZF and MZF has derived under the comprehensive model of imperfect bandwidth information.

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.

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.

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.

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.

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.