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Summary: In this paper, a non‐orthogonal multiple access (NOMA)‐based precoded quadrature spatial modulation (PQSM) technique (NOMA‐PQSM) has been proposed for the downlink scenario. In NOMA‐PQSM, two intended receiving antennas are activated at any time instant. One antenna is activated for the in‐phase component of the transmitted signal, and another one is activated for the quadrature phase component, on the basis of data bits. NOMA‐PQSM provides benefits like improved spatial diversity and spectral efficiency in comparison with spatial modulation. This work uses zero forcing (ZF) precoding over downlink flat fading Rayleigh multiple input multiple output (MIMO) channels, to limit the channel's deteriorating effect on transmitted signal, assuming perfect channel state information (CSI) at the transmitter. A low complexity receiver based on the successive interference cancellation is used. An expression for the upper bound of average bit error probability is derived. Moreover, the expressions for the sum mutual information of users and its lower bound are also derived. The proposed scheme is compared with the preprocessing aided spatial modulation (PSM)‐based counterpart. Monte Carlo simulations reveal that the NOMA‐PQSM scheme outperforms its orthogonal counterpart and the PSM scheme. [ABSTRACT FROM AUTHOR]

The rapid development of wireless communication in today's society is facing the development bottleneck of increasingly tense spectrum resources. As the key technology of 5G technology, Massive Multiple Input Multiple Output (MMIMO) technology has been widely studied and applied in recent years. It is expected to bring progress to wireless communication systems. The key characteristic of MMIMO is its large antenna array that results in a high dimension of the wireless system channel. This article examines the use of precoding technology in large-scale multi-antenna MIMO systems to address the issue of Common Channel Interference (CCI). The study starts by introducing the concept of linear digital precoding and provides mathematical demonstrations of three linear digital precoding schemes. The performance of these schemes is then simulated and analyzed using MATLAB, with the results showing a significant improvement in the bit error performance and combining rate of the MIMO system. [ABSTRACT FROM AUTHOR]

Precoding is a critical signal processing technique used in wireless communication systems to enhance transmission performance. This paper initially provides a brief overview of various conventional precoding algorithms. The exploration includes various nonlinear precoding algorithms which outperform linear techniques in high signal-to-noise ratio (SNR) scenarios. Moreover, the paper delves into practical considerations and provides insights into selecting the most suitable technique for specific communication scenarios. The deep learning-based hybrid precoder is designed using the MDL-AltMin algorithm and simulated results show a spectral efficiency of (SE) 40.96 dB compared with different precoding algorithms. The precoder model is modified with a Hybrid Precoding Net algorithm with a spectral efficiency of 21.07 dB for high values of SNR such as −30 and again compared with deep learning precoders. The HPNet model is proposed with a spectral efficiency of 23.04 dB with and without CSI (Channel State Information) at the transmitter. Furthermore, the HPNet model is compared with optimal digital precoders. [ABSTRACT FROM AUTHOR]

This paper discusses the operation of a massive multiple‐input multiple‐output (MIMO) system from a different perspective. The system is performed in the presence of an eavesdropper who is trying to disrupt the message being transmitted between the base station (BS) and the users. An attempt has been made to maximize the secure energy efficiency (EE) of the system by allocating appropriate power to each user. The channel state information (CSI) between users and the BS is considered imperfect and the employed precoding scheme is the zero forcing (ZF). The CSI related to the eavesdropper is considered to be perfect and its precoding is assumed to be the maximum ratio transmission (MRT). The problem of optimization that is for maximizing the EE has two constraints including the maximum transmission power and the minimum user data rate. To improve the performance of system, the cell division technique is applied, which results in approaching the performance of system to the without eavesdropper scenario. Five various scenarios have been investigated in this research, and it is proved that the proposed method improves the system performance in all cases. The numerical and simulation results obtained from implementation of the proposed algorithm confirm the claim. [ABSTRACT FROM AUTHOR]

The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless multiple inputs and multiple outputs (MIMO) systems. In our work, we approximate the target Spectral Efficiency function with a novel computationally simpler function. Then, we reduce the precoding problem to an unconstrained optimization task using a special differential projection method and solve it by the Quasi-Newton L-BFGS iterative procedure to achieve gains in capacity. We are testing the proposed approach in several scenarios generated using Quadriga-open-source software for generating realistic radio channel impulse response. Our method shows monotonic improvement over heuristic methods with reasonable computation time. The proposed L-BFGS optimization scheme is novel in this area and shows a significant advantage over the standard approaches. The proposed method has simple implementation and can be a good reference for other heuristic algorithms in this field. [ABSTRACT FROM AUTHOR]

Modern 5G wireless cellular networks use massive multiple-input multiple-output (MIMO) technology. This concept entails using an antenna array at a base station to concurrently service many mobile devices that have several antennas on their side. In this field, a significant role is played by the precoding (beamforming) problem. During downlink, an important part of precoding is the power allocation problem that distributes power between transmitted symbols. In this paper, we consider the power allocation problem for a class of precodings that asymptotically work as regularized zero-forcing. Under some realistic assumptions, we simplify the spectral efficiency functional and obtain tractable expressions for it. We prove that equal power allocation provides optimum for the simplified functional with total power constraint (TPC). We propose low-complexity Intersection methods (IM) that improve equal power allocation in the case of per-antenna power constraints (PAPC). On simulations using Quadriga, the proposed IM method in combination with widely-studied water filling (WF) shows a significant gain in spectral efficiency while using a similar computing time as the reference equal power (EP) solution. [ABSTRACT FROM AUTHOR]

Beamspace MIMO-NOMA is an effective way to improve spectral efficiency. This paper focuses on a downlink non-orthogonal multiple access (NOMA) transmission scheme for a beamspace multiple-input multiple-output (MIMO) system. To increase the sum rate, we jointly optimize precoding and power allocation, which presents a non-convex problem. To solve this difficulty, we employ an alternating algorithm to optimize the precoding and power allocation. Regarding the precoding subproblem, we demonstrate that the original optimization problem can be transformed into an unconstrained optimization problem. Drawing inspiration from fraction programming (FP), we reconstruct the problem and derive a closed-form expression of the optimization variable. In addition, we effectively reduce the complexity of precoding by utilizing Neumann series expansion (NSE). For the power allocation subproblem, we adopt a dynamic power allocation scheme that considers both the intra-beam power optimization and the inter-beam power optimization. Simulation results show that the energy efficiency of the proposed beamspace MIMO-NOMA is significantly better than other conventional schemes. [ABSTRACT FROM AUTHOR]

Hybrid precoding can significantly reduce the number of required radio frequency (RF) chains in massive MIMO systems. However, due to the large number of antennas and the high‐dimensional channel, the existing hybrid precoding algorithms usually require very high complexity. In this paper, we propose a convolutional neural network (CNN)‐based hybrid precoding scheme by utilizing unsupervised learning to reduce both the computational complexity and space complexity. Specifically, we first design a low‐complexity CNN structure to achieve the analog precoder, where the size of the convolution kernel and the number of channels are reduced by the further improved inception network. Then, we obtain the digital precoder by the classical zero‐forcing (ZF) algorithm. Simulation results show that, the proposed CNN‐based hybrid precoding can approach the sum‐rate performance of the classical two‐stage hybrid precoding but has much lower complexity. [ABSTRACT FROM AUTHOR]

Due to the limitation of mobility and cost, it is inappropriate to utilize ground base station (GBS) to provide service in emergency scenarios or harsh environments. Unmanned aerial vehicle (UAV) is considered as a feasible way to solve the problem. Millimetre wave communication and UAV can be used together to offer wireless communications flexibly and rapidly for target area. However, fuselage jittering and energy supply would affect the quality and reliability of UAV communication seriously. To overcome the weakness of UAV, the authors prefer to use multiple UAVs to provide wireless communication service simultaneously. This paper investigates the design of hybrid beamforming in the scenarios including multiple UAVs and one end user. Cooperation strategy and alternating optimization method are applied in this design. The distributed UAV base stations are regarded as an entirety and the reference beamforming scheme obtained. Then, the beamforming problem for each UAV is formulated. Moreover, residual error minimization (REM) algorithm is proposed to find the solution of hybrid beamformers at UAV side. Finally, the beamformer of the receiver is optimized with the assist of effective channel, which includes the gain of both channel and beamformers of the transmitters. Simulation results show that the proposed algorithm can achieve near‐optimal spectral efficiency in different scenarios. [ABSTRACT FROM AUTHOR]

Wireless communication over Multiple Input and Multiple Output (MIMO) channel achieve increased transmission rate by dividing the input stream into a multitude of parallel data streams which are transmitted in parallel. Precoding at the transmitter aims to decompose the channel into an uncorrelated multiple subchannels using the channel decomposition technique so that data streams will be sent in parallel independent subchannels. The proposed analysis is to analyze the performances of the MIMO precoder using various channel decomposition algorithms are compared and its computational complexity is analyzed. The channel decomposition schemes considered are Singular Value Decomposition, Geometric Mean Decomposition, LDLH, LU, Schur, QR and Jordan decomposition. The simulation and analytical results confirm that precoding for the MIMO channel decomposed by the QR scheme outperforms all the other precoding methods based on channel decomposition in the light of Bit Error Rate performance and involves a relatively lesser number of Floating Point Operations. [ABSTRACT FROM AUTHOR]

This paper proposes combined precoding and artificial noise‐insertion scheme to enhance the secrecy of generalized precoded spatial modulation when the wiretap channel is partially correlated with the legitimate channel. It is shown that randomizing the modulated and spatial symbols prior to artificial noise insertion can significantly enhance secrecy even with a highly correlated eavesdropper channel. The proposed scheme exploits the channel state information (CSI) of the legitimate channel without requiring knowledge of the eavesdropper channel. The security of the proposed system depends on the amount of power allocation and the number of active receive antennas. Simulation results validate the proposed security scheme and show that the hybrid approach proposed outperforms the one that relies on artificial noise transmission. [ABSTRACT FROM AUTHOR]

The sixth generation advocates green communications, thus energy efficiency (EE) has become an important metric. In this study, a method to increase the EE of a reconfigurable intelligent surface (RIS) aided point‐to‐point communication system is proposed, where both sources are equipped with multi‐antenna and operate in the full‐duplex (FD) mode. The extra power consumption for self‐interference cancellation in the FD mode is considered and modelled as a linear function of the transmission power. The EE maximisation problem is divided into an active beamforming subproblem for the two multi‐antenna sources and a passive beamforming subproblem for RIS, and an alternative optimisation framework is adopted to solve them iteratively. Dinkelbach's method is used to address the fractional objective function in the active beamforming optimisation problem. The penalty method and successive convex approximation are exploited for passive beamforming design. Simulation results show that the scheme can greatly boost the EE performance compared with the half‐duplex mode and is superior to the sum‐rate‐maximisation scheme in larger transmission power settings. The proposed method can be used to extend the lifetime of communication devices without deteriorating communication performance. [ABSTRACT FROM AUTHOR]

The design of an optimal non‐orthogonal multiple access (NOMA) transmission scheme with finite alphabet inputs for a typical two‐user uplink wireless communication system is investigated in which each terminal is equipped with a single antenna. Each of the two users utilises a four quadrature amplitude modulation (4‐QAM) constellation to transmit information data to a common base station, and the receiver employs a maximum likelihood (ML) detector to jointly estimate both transmitted signals. Assuming the availability of channel state information at both the transmitters and the receiver, it is aimed to design a pair of scalar beamformers for the two users such that the minimum Euclidean distance between elements of the received sum‐constellation is maximised subject to the power constraints on the users. A thorough consideration of all the different conditions results in the derivation of a closed‐form optimal beamformer design. As well, examination of the construction of sum‐constellation resulted from the optimum design directly leads to the unique decoding of the original transmitted signal of each user. To facilitate practical implementation, a fast decoding procedure of the optimum NOMA scheme is further developed. The corresponding theoretic probability of ML detection error is also derived. The theoretical development of an optimum sum‐constellation for the basic 2‐user 4‐QAM system provides a solid platform for the derivation of an optimum sum‐constellation for a K‐user and/or M‐QAM system. Indeed, a simple development of the basic sum‐constellation map facilitates such extensions. Numerical simulations not only demonstrate that the performance of the fast decoder agrees closely with the theoretical analysis, but also verify that it is superior in performance to other existing NOMA designs for the same system under high signal‐to‐noise ratio. [ABSTRACT FROM AUTHOR]

Massive multiple input multiple output (Ma-MIMO) is one of the basic enabler technologies for 5 G wireless communication networks to provide higher spectral efficiency (SE) by using large number of antennas and serves many users simultaneously in the same frequency--time resources. In a time division duplex (TDD) Ma-MIMO downlink (DL) system, the base station (BS) estimates the channel using uplink (UL) training but a pilot contamination (PC) is the major challenge in multi-cell Ma-MIMO system. This challenge causes severe inter-cell interference at the home cell and then limits the performance of the system. Precoding techniques with pilot reuse factor (PRF) are used to mitigate the PC effect. The performance of DL multi cell Ma-MIMO system is analyzed under spatial correleted Rayleigh fading channel with both perfect and imperfect channel state information (CSI). Precoding is used to mitigate the intra-cell interferences and PRF reduces the PC effect by assigning orthogonal pilots to neighboring cells. SE performance of multi cell Ma-MIMO system is analyzed with maximum ratio transmitter (MRT), zero forcing (ZF) and minimum mean square error (MMSE) precoding techniques and combined with PRF. Performance comparison of precoding techniques showed that MMSE provides the best SE performance for both CSI and it has highest SE at PRF of four among all when the number of antennas are changed. When both the number of users (K) and antennas (M) are increased simultaneously and M>>K, the SE is improved by more than 25% and also system performance with perfect CSI is better than imperfect CSI. [ABSTRACT FROM AUTHOR]

This paper proposes a novel spread spectrum and sub-carrier index modulation (SS-SIM) scheme, which is integrated to orthogonal frequency division multiplexing (OFDM) framework to enhance the diversity over the conventional IM schemes. Particularly, the resulting scheme, called SS-SIM-OFDM, jointly employs both spread spectrum and sub-carrier index modulations to form a precoding vector which is then used to spread an M-ary complex symbol across all active sub-carriers. As a result, the proposed scheme enables a novel transmission of three signal domains: SS and sub-carrier indices, and a single M-ary symbol. For practical implementations, two reduced-complexity near-optimal detectors are proposed, which have complexities less depending on the M-ary modulation size. Then, the bit error probability and its upper bound are analyzed to gain an insight into the diversity gain, which is shown to be strongly affected by the order of sub-carrier indices. Based on this observation, we propose two novel sub-carrier index mapping methods, which significantly increase the diversity gain of SS-SIM-OFDM. Finally, simulation results show that our scheme achieves better error performance than the benchmarks at the cost of lower spectral efficiency compared to classical OFDM and OFDM-IM, which can carry multiple M-ary symbols. [ABSTRACT FROM AUTHOR]

Cell-free massive multiple-input multiple-output (mMIMO) systems are an alternative topology for mMIMO deployment, wherein a large number of access points are distributed over the coverage area to jointly serve users. Linear precoding methods such as zero-forcing are sufficient to achieve near-optimal performance in mMIMO systems. However, a key challenge in implementing these precoders can be a channel matrix inversion operation, which results in significant computational complexity in systems with large-scale antenna arrays. Hence, instead of direct matrix inversion, we examine several iterative methods to calculate the precoding matrix in a cell-free mMIMO system. We investigate their computational complexity and convergence rate in the presence of small- and large-scale fading and spatial correlation between antennas. Notably, we demonstrate that some iterative methods previously proposed for conventional (co-located) mMIMO do not always converge for cell-free mMIMO. Our main focus is the hyper-power iterative inversion method, which can be applied to both matrix inverses and pseudoinverses with guaranteed convergence; its factorized version also reduces its computational complexity. Although the hyper-power method does not reduce the complexity compared to direct matrix inversion, it converges quickly with high accuracy and strong numerical stability, and is conducive to parallel computation. These qualities make it a good candidate for matrix inversion in cell-free mMIMO system precoders. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRSs) enhance the robustness of wireless transmissions against shielding. However, addressing channel-estimation overheads caused by the large number of IRS elements remains a major challenge. In particular, these overheads increase proportionately with an increase in the number of IRS elements, thereby making it difficult to handle multiple IRSs. Therefore, we investigate a passive beamforming method with partial channel state information (CSI) in distributed IRS communication systems called selective reflection control (SRC). Specifically, the proposed method determines the associations between the IRS and user equipment (UE) to obtain the CSI of the associated IRS-UE links. Simulations were conducted, and the obtained results confirm that the proposed method based on SRC outperforms the benchmark method in terms of the user sum rate. Furthermore, the proposed method realizes robust transmissions against shielding owing to appropriate IRS–UE associations. Therefore, the proposed SRC achieves better communication performance with less channel estimation overheads, which is expected to accelerate large-scale IRS deployment. [ABSTRACT FROM AUTHOR]

In this article, a linear precoding weight vector is designed to enhance the minimum signal-to-interference plus noise ratio (SINR) of a space-time line code (STLC)-based multicast users. To solve the intractable minimum SINR maximization problem, the optimal weight vector for each STLC user is derived, and then, the individual optimal weight vectors are linearly combined. The designed linear precoding vector improves the minimum and average SINR of the multicast users as verified by numerical results. Numerical results also verify that the STLC-based multicast is a promising scheme, especially, if a transmitter has a large number of transmit antennas and the additive noises are severe at the users. [ABSTRACT FROM AUTHOR]

We consider a cell-free massive multiple-input multiple-output (MIMO) system with multi-antenna access points and user equipments (UEs) over Weichselberger Rician fading channels with random phase-shifts. More specifically, we investigate the uplink spectral efficiency (SE) for two pragmatic processing schemes: 1) the fully centralized processing scheme with global minimum mean square error (MMSE) or maximum ratio (MR) combining; 2) the large-scale fading decoding (LSFD) scheme with local MMSE or MR combining. To improve the system SE performance, we propose a practical uplink precoding scheme based on only the eigenbasis of the UE-side correlation matrices. Moreover, we derive novel closed-form SE expressions for characterizing the LSFD scheme with the MR combining. Numerical results validate the accuracy of our derived expressions and show that the proposed precoding scheme can significantly improve the SE performance compared with the scenario without any precoding scheme. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) transmission scheme for hybrid millimeter-wave (mmWave) system and study its user grouping and power allocation. In order to maximize the weighted sum-rate (WSR) of the system, we first propose a user grouping algorithm based on min-sum message passing (MSMP) strategy under the limited number of radio frequency (RF) chains. Then, with the zero-forcing (ZF) digital precoding, we propose a power allocation scheme for multiple-RF-chain NOMA (MRFC-NOMA) structure based on a non-convex transformation method, and design a low-complexity algorithm. The simulation results show that the proposed joint user grouping and power allocation method with lower complexity can achieve better WSR performance than the traditional schemes. [ABSTRACT FROM AUTHOR]

We analyze the secrecy performance of a wireless system with limited feedback, where the channel state information (CSI) is imperfectly known at a multi-antenna source. In order to mitigate the adverse effects of limited feedback and eavesdropper attack on secrecy transmission, we propose the quantized secrecy precoding (QSP) oriented adaptive transmit antenna selection (ATAS) scheme denoted as QSP-ATAS, where the transmit antennas with poor channel quality are inactivated by adjusting the channel gain threshold. Besides, the conventional single transmit antenna selection (STAS) scheme without secrecy precoding (NSP-STAS), where only the optimal transmit antenna has the chance to be selected for transmission, is considered as a baseline. Since that both the number of active transmit antennas and the number of quantization bits affect the quantization error, we define the effective secrecy throughput as the difference between the secrecy data rate and feedback rate to evaluate the system performance. We conduct an effective secrecy throughput analysis for both QSP-ATAS and NSP-STAS schemes and show the existence of the maximal effective secrecy throughput of proposed QSP-ATAS scheme. Furthermore, an optimization analysis of the QSP-ATAS scheme is carried out for the sake of further improving the effective secrecy throughput with regard to the channel gain threshold. Numerical simulation results demonstrate that our proposed QSP-ATAS scheme performs better than the conventional NSP-STAS scheme in terms of the effective secrecy throughput. [ABSTRACT FROM AUTHOR]

It is challenging to monitor suspicious links in massive multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems with directional beamforming. When the monitor and suspicious user are not in the coverage of the same beam, to implement legitimate monitoring, we propose the proactive eavesdropping scheme in which the monitor acts as a spoofing relay to realize beam misleading and data eavesdropping. In the phase of beam sweep, the beam misleading algorithm induces the transmitter to choose the beam which is beneficial to the monitor by optimizing the relay precoding matrices. In the phase of data transmission, the data eavesdropping algorithm elevates the monitoring rate by optimizing the relay power split factors and power gain factors of all subcarriers. Due to the unknown channel state information between suspicious pairs, we propose to find the optimal precoders and power split factors by the multi-agent deep deterministic policy gradient (MADDPG) algorithm. The simulation results verify the effectiveness and superiority of the proposed eavesdropping scheme. [ABSTRACT FROM AUTHOR]

In conventional multi-user multiple-input multiple-output (MU-MIMO) systems with frequency division duplexing (FDD), channel acquisition and precoder optimization processes have been designed separately although they are highly coupled. This paper studies an end-to-end design of downlink MU-MIMO systems which include pilot sequences, limited feedback, and precoding. To address this problem, we propose a novel deep learning (DL) framework which jointly optimizes the feedback information generation at users and the precoder design at a base station (BS). Each procedure in the MU-MIMO systems is replaced by intelligently designed multiple deep neural networks (DNN) units. At the BS, a neural network generates pilot sequences and helps the users obtain accurate channel state information. At each user, the channel feedback operation is carried out in a distributed manner by an individual user DNN. Then, another BS DNN collects feedback information from the users and determines the MIMO precoding matrices. A joint training algorithm is proposed to optimize all DNN units in an end-to-end manner. In addition, a training strategy which can avoid retraining for different network sizes for a scalable design is proposed. Numerical results demonstrate the effectiveness of the proposed DL framework compared to classical optimization techniques and other conventional DNN schemes. [ABSTRACT FROM AUTHOR]

The problem of computing the Hamming weight distribution of linear codes is considered in this paper. A novel method to enumerate all codewords up to a certain Hamming weight for binary linear block codes in general and in particular for the punctured, shortened, precoded polar codes is introduced. The proposed approach performs a recursive decomposition of the codes using construction X4 that is typically used to combine codes of different lengths. This allows to enumerate the low-weight codewords of the overall code as combinations of the low-weight codewords of the component codes. Numerical results show that the proposed approach can efficiently compute the exact partial weight distribution of the 5G New Radio punctured/shortened polar codes with CRC11 and pure polar codes. In the former and latter cases, the low-weight codeword number is up to 106 and 108, respectively. Besides, randomly punctured and shortened polar codes and randomly precoded polar codes are also considered. To the best of the authors’ knowledge, this is the first method able to solve these problems. [ABSTRACT FROM AUTHOR]

We consider construction of deletion and substitution correcting codes with low redundancy and efficient encoding/ decoding. First, by simplifying the method of Sima et al. (ISIT 2020), we construct a family of binary single-deletion $s$ -substitution correcting codes with redundancy $(s+1) (2s+1)\log _{2} n+o(\log _{2} n)$ and encoding complexity $O(n^{2})$ , where $n$ is the blocklength of the code and $s\geq 1$. The construction can be viewed as a generalization of Smagloy et al.’s construction (ISIT 2020), and for the special case of $s=1$ , our construction is a slight improvement in redundancy of the existing works. Further, we modify the syndrome compression technique by combining a precoding process and construct a family of systematic $t$ -deletion $s$ -substitution correcting codes with polynomial time encoding/decoding algorithms for both binary and nonbinary alphabets, where $t\geq 1$ and $s\geq 1$. Specifically, our binary $t$ -deletion $s$ -substitution correcting codes of length $n$ have redundancy $(4t+3s)\log _{2}n+o(\log _{2}n)$ , whereas, for $q$ being a prime power, the redundancy of $q$ -ary $t$ -deletion $s$ -substitution codes is asymptotically $\left({4t+4s-1-\lfloor \frac {2s-1}{q}\rfloor }\right)\vphantom {{\lfloor \frac {2s-1}{q}\rfloor }_{j}}\log _{q} n + o(\log _{q}n)$ as $n\to \infty $. We also construct a family of binary systematic $t$ -deletion correcting codes (i.e., $s=0$) with redundancy $(4t-1)\log _{2} n+o(\log _{2} n)$. The proposed constructions improve upon the redundancy of the state-of-the-art constructions. [ABSTRACT FROM AUTHOR]

Multi-numerology transmission is a promising multiple access scheme for flexible communication systems, which can simultaneously support users with different service requirements. To this end, both inter- and intra-numerology interference (inter-NI and intra-NI) should be suppressed, which is not straightforward. This paper proposes a novel zero-forcing (ZF) precoding design, which perfectly eliminates all the interference, for massive multiple-input multiple-output (MIMO) systems with multi-numerology. First of all, we express the signal-to-interference-plus-noise ratio (SINR) of the multi-numerology system with spectrum sharing. From the SINR representation, we identify the channels that precoders must nullify to suppress inter-NI. After that, we propose a ZF precoder suppressing both inter-NI and intra-NI perfectly. The lower bound of ergodic achievable rate with perfect channel state information at the transmitter (CSIT) is analyzed. Based on the lower bound of ergodic achievable rate, we present the feasible rate region. Also, we propose two power allocation schemes: user fairness and the ergodic sum rate maximization. The simulation results demonstrate the advantage of the proposed precoding design and verify our analysis results. [ABSTRACT FROM AUTHOR]

This correspondence considers the performance evaluation of precoded orthogonal frequency division multiplexing (P-OFDM) based on Walsh-Hadamard Transform (WHT) in the presence of symbol timing offset (STO). The signal-to-interference plus noise ratio (SINR) is evaluated for flat and frequency-selective fading channels (FSC), where closed-form analytical expressions are derived for the flat fading case. In FSC, the SINR is obtained using Monte Carlo simulation due to the analysis intractability. The bit error rate (BER) performance of OFDM and P-OFDM based on WHT, Haar, and Zadoff-Chu matrix transforms are considered to demonstrate the STO impact on the BER using various precoding transforms. The obtained results show that the impact of STO on P-OFDM is substantially different from conventional OFDM. In particular, it is found that STO affects the SINR of each subcarrier differently, where the SINR of certain subcarriers is severely degraded while others are immune. Furthermore, the diversity gain advantage of the precoding process may vanish for large STOs. [ABSTRACT FROM AUTHOR]

This paper investigates different precoding strategies for rate splitting multiple access (RSMA) in the downlink of multi-cell visible light communication (VLC) networks. Since classical Shannon capacity formula does not hold for VLC, we first provide a lower bound on the channel capacity for RSMA in such interfering networks. Then, we formulate a spectral efficiency maximization problem to jointly find the optimal rate-splitting and transmit precoding. Beside that, since cell-edge users suffer from additional inter-cell interference, we propose to design the precoders of different RSMA signals utilizing coordinated beamforming (CB). Subsequently, aiming to improve the performance of the CB design for RSMA, while maintain a reduced complexity, we introduce two enhanced precoding strategies for RSMA. To the best of the authors’ knowledge such a contribution has not been considered before in the open literature. It is shown in the paper that the formulated optimization problem is non-convex and a sub-optimal, yet, a low complexity solution can be obtained efficiently using semi-definite relaxation combined with successive convex approximation. Through analytical results, we illustrate the flexibility and superiority of the proposed precoding strategies for RSMA over conventional coordinated space division multiple access and non-orthogonal multiple access for different scenarios and network loads. [ABSTRACT FROM AUTHOR]

Physical layer security is a useful tool to prevent illegal wiretapping to confidential information. In this paper, we consider a generalized model of conventional physical layer security, referred as hierarchical information accessibility (HIA). A main feature of the HIA model is that a network has a hierarchy in information access, wherein decoding feasibility is determined by each user’s priority. Under this HIA model, we formulate a sum secrecy rate maximization problem with regard to precoding vectors. This problem is challenging since multiple non-smooth functions are involved into the secrecy rate to fulfill the HIA conditions and also the problem is non-convex. To address the challenges, we approximate the minimum function by using the LogSumExp technique, thereafter obtain the first-order optimality condition. One key observation is that the derived condition is cast as a functional eigenvalue problem, where the eigenvalue is equivalent to the approximated objective function of the formulated problem. Accordingly, we show that finding a principal eigenvector is equivalent to finding a local optimal solution. To this end, we develop a novel method called generalized power iteration for HIA (GPI-HIA). Simulations demonstrate that the GPI-HIA significantly outperforms other baseline methods in terms of the secrecy rate. [ABSTRACT FROM AUTHOR]

To reduce the computational complexity and channel estimation overhead for multi-intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication, we consider a joint design of the hybrid precoders at the base station and the passive precoders at the IRSs to maximize the ergodic spectral efficiency by exploiting the twin-timescale channel state information (CSI). Specifically, the digital precoder is designed according to the instantaneous CSI of a reduced-dimensional assist channel matrix, while the IRS passive reflection coefficient matrices and the analog precoder are optimized using the statistical CSI of all links. However, such a design problem is challenging to solve due to the non-convexity and the twin timescale. This work proposes efficient algorithms to jointly design the precoders, where the update of the IRS reflection coefficient matrices is independent of the hybrid precoders and the design of the analog precoder is independent of the digital precoder. Simulation results demonstrate the effectiveness of the proposed algorithms and provide the application scenes of the fully-connected and subarray-connected architectures. The results also show that the ergodic spectral efficiency for the fully-connected architecture using the twin-timescale CSI can approach that using the existing CSI schemes with less channel estimation overhead and computational complexity. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer can be achieved using an integrated receiver, where the incoming signal is rectified, and both the energy harvesting (EH) and the information detection (ID) operate on this rectified signal. Because phase information is lost at the input of the ID, commonly-used modulation techniques cannot be straightforwardly applied and biased $M$ -ASK is used instead. We consider downstream communication over a Rician block-fading channel, from a multi–antenna basestation to a number of single-antenna users. Multi-user interference is eliminated by applying zero-forcing precoding. Using a realistic rectifier model, we compare EH and ID performances of linear precoding (LP) and modified Tomlinson-Harashima precoding (THP). We add low-complexity algorithms to these precoders that optimize the user ordering and the constellation rotations. Moreover, we investigate the effect of the amplitude ratio $\rho _{\mathrm {ASK}}$ of the constellation on the energy-rate trade-off. Compared to the same precoders without optimization, optimizing the user ordering, rotations and $\rho _{\mathrm {ASK}}$ considerably reduces the transmit power required to achieve a harvested power of −30 dBm or an average mutual information of $(\log _{2}M)/2$. Both with and without optimizations, THP outperforms LP in terms of EH and ID, but THP exhibits much larger gains when optimizations are applied. [ABSTRACT FROM AUTHOR]

5G systems are becoming a reality and the evolution toward beyond 5G and 6G systems is already being defined, also to cope with the ever increasing capacity demanded by on-ground users. This will pose challenging requirements on the feeder link of future satellite systems, which risks to become a bottleneck for the overall system performance. In this article, we propose a novel architecture of linear precoding for the feeder link of a broadcast satellite system operating with full frequency reuse to significantly enhance the achievable capacity. The architecture has been simulated and tested in a challenging multifrequency scenario, where Ku, Ka, Q/V, and W bands have been considered for transmission. The numerical performance analysis and the open issues related to the practical realization of the proposed architecture are also thoroughly discussed. [ABSTRACT FROM AUTHOR]

This article investigates the impact of precoding on the performance of massive multiple-input multiple-output (mMIMO) transmitters exhibiting nonnegligible antenna crosstalk. For this, a new metric, called the average active impedance, is introduced to quantify the extent of load modulation as a function of the antenna S-parameters and the employed precoding. The new metric is then used to investigate the load modulation under conventional precoding schemes. It is shown that these precoders yield large disparities in average-power levels across the radio frequency (RF) chains, which results in substantial performance variations with channel conditions. Based on this investigation, we propose three new precoding schemes that yield equal average-power (EP) levels across all RF chains, independent of the channel conditions. Numerical simulations and experiments conducted on an mMIMO transmitter prototype confirmed that the proposed schemes improve the transmitter’s resilience to the variation in channel conditions. [ABSTRACT FROM AUTHOR]

This article investigates the performance of intelligent reflective surfaces (IRS)-aided physical layer network coding (PNC) in two-way relaying channels (TWRC). Specifically, IRS is used to eliminate carrier phase offset (CPO) at the relay node. To this end, the IRS reflectors’ phase shifts are optimized to align the received signals from two source nodes at the relay. This facilitates using a simple mapping function at the relay to map the superimposed signal to a network-coded signal. Two scenarios are considered, the first of which assumes that each source node is served by a separate IRS panel, while the second scenario considers the more challenging case where only one IRS panel is available for the two source nodes. In the latter case, the IRS panel is seen by both source nodes and its phase shifts are optimized to mitigate the CPO problem while maximizing the received signal amplitude at the relay. This optimization problem is formulated and solved over the complex circle manifold. Finally, we extend the IRS-assisted PNC system to include channel coding and higher modulation orders, for which a repeat accumulate (RA) channel-coded IRS-aided PNC scheme is proposed for general quadrature amplitude modulation (QAM) signals. A belief propagation (BP) based algorithm is designed to decode the network-coded sequences over a q-Ring using modular arithmetic. Our simulation results validate the theoretical error expressions derived for the two-IRS scenario as well as the efficacy of the proposed manifold optimization approach for the one-IRS scenario. The results also confirm the efficacy of the designed channel-coded IRS-aided PNC using high QAM modulation orders. [ABSTRACT FROM AUTHOR]

The massive multiple-input multiple-output (MIMO) transmission technology has recently attracted much attention in the non-geostationary, e.g., low earth orbit (LEO) satellite communication (SATCOM) systems since it can significantly improve the energy efficiency (EE) and spectral efficiency. In this work, we develop a hybrid analog/digital precoding technique in the massive MIMO LEO SATCOM downlink, which reduces the onboard hardware complexity and power consumption. In the proposed scheme, the analog precoder is implemented via a more practical twin-resolution phase shifting (TRPS) network to make a meticulous tradeoff between the power consumption and array gain. In addition, we consider and study the impact of the distortion effect of the nonlinear power amplifiers (NPAs) in the system design. By jointly considering all the above factors, we propose an efficient algorithmic approach for the TRPS-based hybrid precoding problem with NPAs. Numerical results show the EE gains considering the nonlinear distortion and the performance superiority of the proposed TRPS-based hybrid precoding scheme over the baselines. [ABSTRACT FROM AUTHOR]

The current cellular systems are conventional cell-centric based architectures, and thus the inter-cell interference greatly affects the quality of service (QoS) of users located at the border of those service areas. For that reason, future wireless systems will rely on a cell-less deployment by using an alternative promising network infrastructure known as cell-free (CF) technology. Here, in contrast to the current networks, there are no concepts of cells or cell boundaries since it is a disruptive paradigm where a large number of geographically distributed access points (APs) simultaneously and jointly serve a much smaller number of user terminals (UTs) to fulfill the exponentially increasing number of users. Therefore, this paper aims to contribute on this field and considers the design of hybrid analog/digital multi-user equalizer for broadband millimeter wave (mmWave) CF massive multiple-input multiple-output (mMIMO) systems, using a distributed beamforming approach (processing is distributed by APs and central unit (CU)) to reduce the fronthaul requirements. First, only a low complexity analog precoder is applied to the transmitter, while a joint design of APs hybrid equalizer and CU combiner are considered by minimizing the average mean square error (MSE) between the transmitted and CU estimated signals. To achieve this joint design, a cyclic minimization method is used to iterate between APs hybrid equalizer and CU combiner, where the information is exchanged between APs and CU based on a set of error variances to improve detection performance. The simulation results show that the proposed precoder and the hybrid linear equalizer can achieve performance results very close to those of the fully digital system. Moreover, just two iterations of the proposed algorithm are already enough to match the full centralized approach performance. [ABSTRACT FROM AUTHOR]

In this paper, we consider a status updating system where updates are generated at a constant rate at $K$ sources and sent to the corresponding recipients through a noise-free broadcast channel. We assume that perfect channel state information (CSI) is available at the transmitter before each transmission, and the transmitter is able to utilize the CSI to precode the updates. Our object is to design optimal precoding schemes to minimize the summed average age of information (AoI) at the recipients. Under various assumptions on the size of each update $B$ , the number of transmit antennas $M$ , and the number of receive antennas $N$ at each user, this paper identifies the corresponding age-optimal precoding and transmission scheduling strategies. Specifically, for the case when $N=1$ , a round-robin based updating scheme is shown to be optimal. For the two-user systems with $N>B$ or $M\notin [N:2N]$ , framed updating schemes are proven to be optimal. For other cases in the two-user systems, a framed alternating updating scheme is proven to be 2-optimal. [ABSTRACT FROM AUTHOR]

Rate-splitting multiple access (RSMA) has recently appeared as a powerful technique for improving the downlink performance of multiple-input multiple-output systems. By flexibly managing interference, RSMA can deliver high spectral and energy efficiency, as well as robustness to imperfect channel state information. In another development, an intelligent reflecting surface (IRS) has emerged as a method to control the wireless environment through software-configurable, near-passive, sub-wavelength reflecting elements. This article presents the potential of synergy between IRS and RSMA. Three important improvements achievable by IRS-RSMA schemes are identified, supported by insightful numerical examples, and mapped to beyond 5G use cases, along with future research directions. [ABSTRACT FROM AUTHOR]

This paper proposes a massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system based on cognitive radio (CR) networks. To reduce the users interference, we propose an efficient user clustering algorithm. Within a cluster, we consider the user with the weak channel gain as a primary user (PU) and the user with the strong channel gain as a secondary user (SU). Given the quality of service for both PUs and SUs, we propose a power allocation (PA) method that maximizes the sum rate. The PA optimization problem is discussed into three scenarios which depend on the available transmit power. Thereafter, we derive a robust solution for the PA issue under imperfect channel state information (CSI) assumptions. Simulation results demonstrate that our proposed NOMA-CR scheme can significantly improve the spectral efficiency (SE). In addition, the proposed robust PA scheme for the imperfect CSI case reduces the performance loss due to the channel uncertainty. [ABSTRACT FROM AUTHOR]

When the channel state information is available, frequency-domain precoding is studied for rectangularly-pulsed orthogonal frequency-division multiplexing (OFDM) using cyclic prefix over dispersive channels to provide extremely compact signal spectrum, enhanced achievable data rate (ADR), and reduced peak-to-average power ratio (PAPR) jointly. With a precoding rate not larger than $1-2I/N$ , a general precoder form is first developed for the transmitted $N$ -subcarrier OFDM signal to provide extremely small baseband power spectral sidelobes decaying asymptotically as $f^{-2I-2}$ or faster, with $f$ being the frequency, and thus achieve high spectrum compactness while yielding reduced PAPR. Incorporating the channel response, a particular spectral precoder following the general form is then designed to maximize the ADR under a fixed transmitted power. When a small out-of-band power proportion is required to guarantee spectrum compactness, the proposed pre-equalized and spectrally-precoded OFDM system can provide much higher ADR per unit bandwidth than pre-equalized OFDM, spectrally-precoded OFDM, and nonprecoded OFDM. When the low-complexity receiver is mandatory, a systematically pre-equalized and spectrally precoded OFDM system is also developed to achieve enhanced ADR, extremely high spectrum compactness, and low-complexity receiver operation by trading transmission power on cancellation subcarriers. [ABSTRACT FROM AUTHOR]

Predictor antenna channel measurements from a 64-antenna base station are used to investigate the effects of channel aging on the precoder design for high-mobility users in a non-line-of-sight (NLOS) massive multiple-input multiple-output (M-MIMO) environment. The effects are evaluated in terms of received downlink (DL) signal-to-interference-and-noise ratio (SINR) and the corresponding ergodic capacity bound. A simulated velocity of 150 km/h is used with a carrier frequency of 2.18 GHz. Maximum ratio (MR) and a codebook-based precoders are used to evaluate single-user transmission; and zero-forcing (ZF), regularized zero-forcing (RZF), and minimum mean-squared error (MMSE) precoders are used to evaluate multi-user transmission with up to nine active users in a cell. Furthermore, predictor antenna predictions are evaluated as a mean of combating channel aging. It is also investigated how the predictor antenna can be used during data reception. Simulations show that outdated channel estimates significantly reduce the SINR and consequently the capacity for all investigated transmission techniques. Basic predictor antenna predictions outperform the use of outdated channel estimates for delays larger than 0.6 ms. In single-user transmission, channel prediction can improve the capacity by 6–14%. The gain from multi-user transmission typically disappears when using outdated channel estimates older than 1 ms. In contrast, the use of predictor antennas enables MIMO for these high-mobility users, which is demonstrated to increase the capacity bound by 100% compared to 1 ms old channel estimates. [ABSTRACT FROM AUTHOR]

In this work we study different scheduling problems in the downlink of a Frequency Division Duplex multiuser wireless system that employs a hybrid precoding antenna architecture for massive Multiple Input Multiple Output. In this context, we propose a scheduling framework using Reinforcement Learning (RL) tools, namely Contextual Multi-Armed Bandits (CMAB), that can dynamically adapt themselves to solve three scheduling problems, which are: i) Maximum Throughput (MT); ii) Maximum Throughput with Fairness Guarantees (MTFG), and; iii) Maximum Throughput with QoS Guarantees (MTQG), which are well-known relevant problems. Before performing scheduling itself, we exploit statistical Channel State Information (CSI) to create clusters of spatially compatible User Equipmentss (UEss). This structure, combined with the usage of Zero-Forcing precoding, allows us to reduce the scheduler complexity by considering each cluster as an independent virtual RL scheduling agent. Next, we apply a new learning-based scheduler aiming to optimize the desired system performance metric. Moreover, only scheduled UEss need to feed back instantaneous equivalent CSI, which also reduces the signaling overhead of the proposal. The superiority of the proposed framework is demonstrated through numerical simulations in comparison with reference solutions. [ABSTRACT FROM AUTHOR]

Statisticalprecoding is considered as a promising technique to release the channel state information (CSI) acquisition overhead. This article investigates a linear precoder design for frequency-division duplexing (FDD) massive MIMO downlink with only statistical CSI. We use a beam-based statistical channel model to capture the spatial correlation characteristics of the channels. The objective of the precoder design is to maximize the ergodic sum-rate under total power constraint. Based on the minorize-maximize (MM) algorithm, a stationary solution of the ergodic sum-rate maximization problem can be obtained. The stationary solution is shown to be the same as the optimal solution to a stochastic weighted minimum mean square error (SWMMSE) problem. Further, we establish the approximations for rate expressions with deterministic equivalent. The deterministic equivalents of ergodic rates are only related to the precoding matrices and statistical CSI. According to these closed-form rate expressions, we propose a linear precoder design algorithm and obtain tractable expressions for precoding matrices. Numerical comparisons with the existing precoding approach demonstrate the significant advantages of the developed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose one joint interference alignment and subchannel allocation (JIARA) interference management scheme, aiming at maximizing the number of satisfactory users with different degrees of freedom (DoF) demand in ultra-dense wireless networks, while the existing works only consider the same DoF demands. The original JIARA scheme is equivalent to the maximum $K$ -colorable subgraph (MKCS) problem in graph theory for a given $K$ -colors and the multicoloring demand at each vertex, hence NP-hard. Therefore, we propose one graph theory based low complexity sub-optimal JIARA scheme. Firstly, we propose one virtual allocation of subchannel based scheme to construct transformed the conflict graph, which is applicable for the different DoF demands and different size of the feasible IA group. Furthermore, we propose one greedy multi-coloring based algorithm to determine the maximum number of satisfactory users. Simulation results show that the proposed JIARA scheme outperforms the subchannel resource allocation only scheme. [ABSTRACT FROM AUTHOR]

Rate splitting (RS) systems can better deal with imperfect channel state information at the transmitter (CSIT) than conventional approaches. However, this requires an appropriate power allocation that often has a high computational complexity, which might be inadequate for practical and large systems. To this end, adaptive power allocation techniques can provide good performance with low computational cost. This work presents novel robust and adaptive power allocation technique for RS-based multiuser multiple-input multiple-output (MU-MIMO) systems. In particular, we develop a robust adaptive power allocation based on stochastic gradient learning and the minimization of the mean-square error between the transmitted symbols of the RS system and the received signal. The proposed robust power allocation strategy incorporates knowledge of the variance of the channel errors to deal with imperfect CSIT and adjust power levels in the presence of uncertainty. An analysis of the convexity and stability of the proposed power allocation algorithms is provided, together with a study of their computational complexity and theoretical bounds relating the power allocation strategies. Numerical results show that the sum-rate of an RS system with adaptive power allocation outperforms RS and conventional MU-MIMO systems under imperfect CSIT. [ABSTRACT FROM AUTHOR]

In this paper, we propose a precoded faster-than-Nyquist (FTN) signaling technique for time-domain single-carrier index-modulated symbol transmission. More precisely, eigenvalue decomposition (EVD) precoding is adopted for the FTN transmission of data bits modulated by single-carrier time-domain index modulation (IM). While the FTN scheme increases the spectral efficiency and data rate by increasing the density of transmit symbols, the time-domain IM works towards the same objective while maintaining symbol sparsity. We analytically derive the constrained capacity of the proposed system. Our simulation results show that the proposed scheme has better bit error ratio (BER) performance than the conventional FTN-IM scheme, particularly for the scenario of a higher packing ratio. With the proposed scheme, a 2.5 dB performance gain is observed at the BER of 10−4, where the packing ratio is 0.7 and the roll-off factor is 0.5 in the channel-uncoded scenario. We further analyze our scheme’s performance by characterizing its minimum Euclidean distance and inter-symbol interference. Furthermore, we present a three-stage serially concatenated iterative detection architecture for the proposed EVD-FTN-IM signaling scheme. It is demonstrated in our simulations that a near-capacity BER performance is achievable in the proposed turbo-coded FTN-IM scheme. [ABSTRACT FROM AUTHOR]

Symbol-level precoding (SLP), which converts the harmful multi-user interference (MUI) into beneficial signals, can significantly improve symbol-error-rate (SER) performance in multi-user communication systems. While enjoying symbolic gain, however, the complicated non-linear symbol-by-symbol precoder design suffers high computational complexity exponential with the number of users, which is unaffordable in realistic systems. In this paper, we propose a novel low-complexity grouped SLP (G-SLP) approach and develop efficient design algorithms for typical max-min fairness and power minimization problems. In particular, after dividing all users into several groups, the precoders for each group are separately designed on a symbol-by-symbol basis by only utilizing the symbol information of the users in that group, in which the intra-group MUI is exploited using the concept of constructive interference (CI) and the inter-group MUI is also effectively suppressed. In order to further reduce the computational complexity, we utilize the Lagrangian dual, Karush-Kuhn-Tucker (KKT) conditions and the majorization-minimization (MM) method to transform the resulting problems into more tractable forms, and develop efficient algorithms for obtaining closed-form solutions to them. Extensive simulation results illustrate that the proposed G-SLP strategy and design algorithms dramatically reduce the computational complexity without causing significant performance loss compared with the traditional SLP schemes. [ABSTRACT FROM AUTHOR]

Multiuser multiple input multiple output (MU‐MIMO) systems can provide high spectral efficiency (SE) that is achieved with transmit/receive combining schemes at the base station (BS) for downlink (DL) and uplink (UL). So far, various combining schemes for DL were proposed, with the regularized zero forcing (RZF) and Tomlinson–Harashima precoding (THP) being usually considered. In a case of massive MU‐MIMO systems, with a large number of antennas, the matrix inversion operation used in the RZF and THP schemes causes high computational complexity that significantly aggravates implementation and raises its costs. The authors propose a low‐complexity transmit combining scheme for the massive MU‐MIMO systems with time division duplex (TDD), devised in a similar manner as the THP scheme, based on the gram‐Schmidt orthogonalization, and show that it achieves slightly better SE than the THP scheme for the estimated channel state information (CSI), but with a much lower complexity than the THP and RZF schemes.In this paper, a low‐complexity transmit combining scheme for the massive MU‐MIMO systems with time division duplex si proposed, devised in a similar manner as the well‐known Tomlinson‐Harashima precoding (THP) scheme. In order to suppress multiuser interference with a lower computational complexity we here employ the Gram‐Schmidt orthogonalization method. The proposed solution is shown to achieve slightly better performance than THP scheme in the case of the estimated channel state information. [ABSTRACT FROM AUTHOR]

In this paper, we propose a rateless coded transmission scheme for the multi-user downlink of Cloud Radio Access Network (C-RAN). In the network, multiple users are served by a cluster of remote radio heads (RRH), which are connected to the building baseband units (BBU) pool through the fronthaul links with limited capacity. In the proposed transmission scheme, the precoder and compressor at the BBU pool, and the decoding algorithm at the users are designed. To further improve the performance of the proposed transmission scheme, we investigate the joint optimization of the precoder and the degree profiles of the rateless codes implemented at the BBU pool to maximize the sum throughput of the network. Explicitly, the optimization problem is formulated according to the extrinsic information transfer (EXIT) function analysis on the decoding process at the users. We give simulation results on the BER and throughput performance achieved by the proposed rateless coded transmission scheme, which verify the effectiveness of the joint optimization on the degree profiles and the precoder. [ABSTRACT FROM AUTHOR]

This paper considers the hybrid precoder design in millimeter wave (mmWave) multi-input multi-output (MIMO) systems with low-resolution analog phase shifters. Aiming at reducing the complexities of the near-optimal algorithms, we propose a low-complexity multi-user hybrid precoding scheme based on tree-coding-aided adaptive-cross-entroy (TC-ACE) algorithm. By defining some discrete variables for the analog precoders and combiners, the problem of hybrid precoding is transformed into a cross-entroy (CE) optimization problem, which can be solved by iteratively updating the probability distributions of the predefined discrete variables. In order to derive the closed-form expression of the probability distributions, tree-coding is used to encode each entry of the analog precoders and combiners with a binary number. Through iterations, optimal analog precoders and combiners will be obtained when its probabilities are sufficiently high. Simulation results show that when the number of users exceeds a certain value, the proposed scheme outperforms the alternating minimization algorithm and coordinate descent method in terms of both the sum-rate and complexity. [ABSTRACT FROM AUTHOR]