Precoding Vectors Research Articles

Resource Allocation for RSMA-Based Coordinated Direct and Relay Transmission

In this letter, we investigate a rate splitting multiple access (RSMA) based coordinated direct and relay transmission (CDRT) system, where a base station (BS) serves two users using the rate splitting strategy, and a decode-and-forward (DF) relay aids the BS in establishing a communication link with a far user. We focus on a max-min fairness problem aiming at maximizing the minimum achievable rate of two users. The precoding vectors of the BS and the relay, the common rate of each user and the time allocation coefficients are jointly optimized under the constraint of limited system resources. Unfortunately, the optimization problem is non-convex due to the coupled optimization variables and the non-convex objective. Therefore, we transform the original problem into a difference of convex (DC) program and obtain a sub-optimal solution by adopting an iterative constrained concave convex procedure (CCCP) based algorithm. Simulation results demonstrate substantial performance gains of our proposed RSMA-CDRT over the conventional CDRT strategies and the flexibility in adapting to various channel environments.

An Enhanced Interference Alignment Strategy With MIL Criterion and RCG Algorithm for IRS-Assisted Multiuser MIMO

An enhanced interference alignment strategy with minimum interference leakage (MIL) criterion and Riemannian conjugate gradient (RCG) algorithm is proposed for intelligent reflecting surface (IRS)-assisted multiuser multiple-input multiple-output (MIMO). In this letter, the maximum sum rate is formulated as the optimization objective, with alternate optimization of phase shift vector at IRS as well as precoding and interference suppression vectors at transceivers respectively. MIL interference alignment criterion is used to iteratively solve the precoding vector and the interference suppression vector via channel reciprocity property. RCG algorithm is further applied to derive the IRS phase shift vector and maximize sum rate with the condition of ensuring a given minimum interference leakage threshold to eliminate system interference. Simulation results reveal that the proposed strategy effectively enhances sum rate performance compared with the scheme using random IRS phase shift vector and random precoding/interference suppression vectors as well as “AP + RCG” scheme in IRS-assisted multiuser single-input single-output (SISO) scenario. In addition, compared with “MMSE + RCG” strategy in the case of same multi-antenna transceiver pairs and antenna numbers, the proposed strategy could make a tradeoff between sum rate performance and computational complexity.

Precoding-Based Handover Scheme Design for High-Speed Railway Communication

In high-speed railway (HSR) communication, the handover becomes more frequent for the high mobility of trains. In this letter, a precoding based handover scheme is proposed to reduce the ping-pong handover trigger rate and improve the HSR system stability. Specifically, the precoding vectors of serving and target cell are jointly designed to maximize the difference in received signal strength between the two cells during the handover preparation phase. And the optimal precoding vectors is solved through the concave-convex process and the second-order cone programming transformation. The simulation results show that the proposed handover scheme can effectively alleviate the occurrence of ping-pong handover and ensure the system stability of HSR communication. The system has higher signal strength than with the traditional scheme.

Decentralized Coordinated Precoding Design in Cell-Free Massive MIMO Systems for URLLC

Cell-free massive multiple-input multiple-output (MIMO) is a promising network to offer huge improvement of the achievable rate compared with conventional cellular massive MIMO systems. However, the commonly adopted Shannon-type achievable rate is only valid in the long block length regime that is not applicable to the emerging short-packet communication. To realize ultra-reliable and low-latency communication (URLLC) in cell-free massive MIMO systems, we optimize the precoding vector at the access points (APs) to maximize the minimum user rate in both the centralized and decentralized fashion. The design takes into account the impact of URLLC and we propose path-following algorithms (PFA) to address the considered problem which generates a sequence of advanced feasible points and converges to at least a locally optimal solution of the design problem. Moreover, we investigate the requirement of the precoding schemes, the length of the transmission duration, the number of antennas equipped at each AP, and the size of each AP cluster on the URLLC rate. Numerical results show that the decentralized PFA precoding can achieve 80% of the 95%-likely URLLC rate of the centralized precoding and 89% of the average URLLC rate with only 12% computational complexity of the centralized precoding.

Model for Interference Evaluation in 5G Millimeter-Wave Ultra-Dense Network with Location-Aware Beamforming

Location-Aware Beamforming (LAB) in Ultra-Dense Networks (UDN) is a breakthrough technology for 5G New Radio (NR) and Beyond 5G (B5G) millimeter wave (mmWave) communication. Directional links with narrow antenna half-power beamwidth (HPBW) and massive multiple-input multiple-output (mMIMO) processing systems allows to increase transmitter and receiver gains and thus facilitates to overcome high path loss in mmWave. Well known problem of pencil beamforming (BF) is in construction of precoding vectors at the transmitter and combining vectors at the receiver during directional link establishing and its maintaining. It is complicated by huge antenna array (AA) size and required channel state information (CSI) exchange, which is time consuming for vehicle user equipment (UE). Knowledge of transmitter and receiver location, UE or gNodeB (gNB), could significantly alleviate directional link establishment and space division multiple access (SDMA) implementation. Background of SDMA is in efficient maintenance of affordable level of interference, and the purpose of this research is in signal-to-interference ratio (SIR) evaluation in various 5G UDN scenarios with LAB. The method, used to evaluate SIR, is link level simulation, and results are obtained from publicly released open-source simulator. Contribution of research includes substantiation of allowable UE density, working with LAB. Practical implications include recommendations on terrestrial and angular separation of two UE in 5G UDN scenarios.

РАЗРАБОТКА НИЗКОРАНГОВЫХ ПРОСТРАНСТВЕННЫХ ВЕКТОРОВ ПРЕДВАРИТЕЛЬНОГО КОДИРОВАНИЯ ВО ВРЕМЕННОЙ ОБЛАСТИ

In this paper we consider the alternative way of development of spatial beamforming processing algorithm in time-domain under low-rank Massive-MIMO systems. It is well-known, that the telecommunication systems, which based on spatial multiplexing technology achieve following advantages: increase the spectral efficiency in many times due to spatial channel multiplexing gain, the beamforming technology implementation (effective energy distribution in the space). The organization of spatial filtering (the beamforming vector processing) – one of the most significant tools in MIMO-OFDM multiplexing. In this paper, we consider a new spatial filtering processing approach (precoding vectors calculation), which is a significant tool in large-scale antenna systems, due to the fact of smart processing of the radio narrow-beam implementation increases the efficiency of the communication system many times over. Nowadays, the spatial filter design algorithms with low computational complexity have attracted considerable attention from researchers seeking to improve existing MIMO-OFDM wireless communication systems. In the paper we developed basic algorithms for calculating precoding vectors in the frequency domain and proposed the time-domain precoder approach with aim to achieve the complexity reduction gain. The proposed method was tested on the geometric statistical simulation channel model QuAdRiGa according to the multipath channel scenario "3GPP-3D Uma-NLoS". We provide the assessment of whole presented methods and the evaluation range of discrepancies was revealed in the form of pictures of the correlation and integral metrics. The analysis of integral cumulative distribution function of simulation results shows the relation gap between accuracy of correlation metric and losses of beamforming processing recalculation approximately -0.5 dB for 1st layer. In conclusion of paper was revealed the fact that proposed SVD factorization for each impulse response did not take into account the beams and eigenvectors distribution over the whole frequency bandwidth

Nonorthogonal Multiple Access Enabled Two-Way Relay System Using Signal Alignment

In the conventional two-way relay nonorthogonal multiple access (TWR-NOMA) system, its diversity order is equal to zero even under the perfect successive interference cancellation (pSIC). In this article, we leverage multiple-input–multiple-output (MIMO) technique in the TWR-NOMA system to extract spatial diversity gain for the performance enhancement. Communications between two user pairs are assisted by a relay. Precoding vectors at users as well as the matrix at the relay are specially designed to perform the signal alignment (SA). We derive analytical closed-form expressions for the outage probability and diversity order with both pSIC and imperfect successive interference cancellation (ipSIC). In addition, the ergodic rate and ergodic sum rate are analyzed. Optimal power allocations for the system outage probability and ergodic sum rate are analyzed based on the quality of service. Simulation results are provided to confirm the derived analytical results. The results show that the combination of SA and TWR-NOMA can decrease the outage probability and improve the diversity order effectively. The ergodic rates finally arise ceilings with both pSIC and ipSIC, and the ergodic sum rate can keep increasing as the power allocated to the distant user increases. However, the conventional TWR-NOMA is complete opposite. In summary, compared to TWR-NOMA, TWR-NOMA-SA has higher diversity order and enables distant users to contribute more to system performance.

Secrecy Rate Optimization in Nonlinear Energy Harvesting Model-Based mmWave IoT Systems With SWIPT

Secrecy rate (SR) optimization in millimeter wave (mmWave) Internet of Things (IoT) systems with simultaneous wireless information and power transfer (SWIPT) is studied in this article. Adopting the SWIPT architecture, energy-constrained devices get charged by the radio-frequency waves transmitted from a base station. The hybrid precoding technique is applied to reduce the implementation cost by separately designing a digital precoder and an analog precoder. Also, we adopt the artificial noise (AN)-assisted transmission method to maximize the SR. In this problem, we aim to jointly optimize the digital precoding vector, AN covariance matrix, and power-splitting ratio under the nonlinear energy harvesting (EH)-constraints. Then, we propose a semidefinite relaxation-based alternating optimization algorithm for the case of perfect channel state information (CSI) and imperfect CSI. Finally, simulation results show that the proposed algorithms are effective to improve the SR.

An Interference-Reducing Precoding for SCMA Multicast Design Based on Complementary Sequences

In a multi-group multicast sparse code multiple access (SCMA) system, one base station multicasts common messages to multiple multicast groups via different code books. To accommodate more user terminals (UTs), traditional multicast systems have multiple transmitters, each of which works in one-to-many mode. In this way, each UT is subject to inter-transmitter interference. Considering the high degrees of freedom for transmitting and receiving, it is difficult to separate the desired signal from interference signals. Therefore, an interference-reducing precoding scheme is required to ensure the reliability of SCMA multicast communication system. For the SCMA multicast system design, we present three necessary conditions that the interference-reducing matrix should satisfy. Then, the precoding matrix satisfying the three necessary conditions simultaneously is designed by utilizing the complementary sequences (CS) and complete complementary sequences (CCS). In this context, we consider two scenarios with different transmission modes (single-cell and multiple-cell) and different precoding schemes (based on CS and CCS). Simulation results show that proposed transmission schemes can significantly reduce the bit error rate of multicast groups while ensuring the communication throughput, and behave a superior performance over other alternatives. Moreover, theoretical and simulation results also prove that the proposed precoding vectors have perfect average power radiation and omnidirectional coverage performance.

Deep frameworks based on residual dense network and reinforcement learning for mmWave massive MIMO systems

SummaryIn millimeter wave (mmWave) massive multiple‐input‐multiple‐output (MIMO) systems, hybrid precoding plays a pivotal role in reducing complexity and cost while providing a good spectral efficiency. However, implementation of digital precoders with large number of antennas is difficult due to hardware constraints, while analog precoders offer confined performance. This leads to high computational complexity and cannot fully exploit the spatial information. Previous studies on hybrid precoding were based on exhaustive search solutions or greedy schemes, which result in higher complexity system performance. To face these challenges, this paper proposes deep hybrid precoding framework with phase quantization and residual dense network to design the matrix of analog and digital precoders. The proposed deep hybrid precoding technique consists of offline training stage and online deployment stage. In offline training stage, hybrid precoding is obtained assuming the approximate phase quantization. While in the online deployment stage, the matrix of analog precoding is calculated by exchanging approximate phase quantization with ideal phase and grouping the analog precoding vectors. In this paper, we also propose a deep reinforcement learning‐based hybrid precoding. It consists of a deep reinforcement learning with employing convolutional neural network and long short‐term memory (LSTM) methods. In our proposed frameworks, structures of proposed techniques are trained for maximum spectral efficiency. Our proposed techniques are compared with other precoding techniques. Results illustrate that the proposed techniques outperforms the other precoding techniques in terms of the spectral efficiency.

Downlink MIMO-RSMA With Successive Null-Space Precoding

In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate optimization problem for the precoding vectors and the associated power allocation for the proposed SNS-based MIMO-rate-splitting multiple access (RSMA) scheme. We obtain a suboptimal solution for this problem via successive convex approximation. Moreover, we study the robustness of the proposed precoding scheme to imperfect channel state information (CSI) at the base station via derivative-based sensitivity analysis. Our analysis and simulation results reveal the enhanced performance and robustness of the proposed SNS-based MIMO-RSMA scheme over several baseline multi-user MIMO schemes, especially for imperfect CSI.

Design of Hybrid Precoding for Millimeter-Wave MIMO-NOMA Systems Based on User Fairness

This letter studies the design of hybrid precoding in millimeter-Wave (mmWave) multiple input multiple output-non orthogonal multiple access (MIMO-NOMA) systems. To guarantee the rate performance for all served users, we formulate the optimization problem of joint analog precoding (AP) and digital precoding (DP) vectors based on maximum and minimum (Max-Min) fairness to maximize the minimal achievable rate of users, i.e., we design different HP vectors for each user from the perspective of fairness. This can be solved by the proposed two-stage optimization scheme. First, the AP matrix and the DP vectors of each user are alternately designed, where the AP and DP vectors can be obtained by using the Semi-Definite Relaxation algorithm and the proposed boundary-compressed particle swarm optimization (BC-PSO) algorithm, respectively. Then, the optimal scaling factors obtained based on the Karush-Kuhn-Tucker (KKT) condition are introduced to further to improve the Max-Min rate. Simulation results show that the proposed scheme performs better than existing schemes.

Linear Precoding for Space-Time Line Code-Based Multicast Systems

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.

Framed Fidelity MAC: Losslessly packing multi-user transmissions in a virtual point-to-point framework

As the number of subscribers in wireless communication systems grows rapidly, it has become important to design efficient medium access control (MAC) protocols to realize resources sharing among multiple users. When designing a MAC, effective management of co-channel interference (CCI) among multiple concurrent transmissions is critical to enhancing system’s spectral efficiency (SE). Although MACs based on existing signal processing can suppress/mitigate CCI among multiple concurrent transmissions, they either consume communication resources or attenuate the desired signals’ transmission, hence incurring loss of transmission performance. To remedy this deficiency, we propose a Framed Fidelity MAC (F2MAC) to losslessly pack multi-user data transmissions into a virtual point-to-point (p2p) framework. Under F2MAC, the common receiver (Rx) selects a virtual framed-channel (a.k.a. framework) and broadcasts it to all mobile terminals. The latter calculate their precoding vectors based on the received virtual framework and their respective communication channels with respect to (w.r.t.) the Rx. Then, the pre-processed signals of multiple users are sent to the Rx via different eigenmodes of the framed-channel. By applying a receive filter to the received mixed signal, Rx can recover users’ desired data without interference. Since F2MAC can decouple the channel quality information (CQI) from channel direction information (CDI) related to the user’s signal transmission, — i.e., CQI is exclusively determined by the user’s communication channel while CDI depends on the unified framework, it can avoid the transmission performance loss incurred by existing signal processing based MAC which adjusts both CQI and CDI simultaneously. Moreover, we propose a Flexible Framed Fidelity MAC (F3MAC) to further improve the system’s SE. By dynamically re-constructing the virtual framed-channel at each mobile user, the user’s transmission can be realized with the principal eigenmode’s gain of his/her communication channel. Our in-depth analysis and simulation results have shown the proposed MAC methods to significantly improve the SE of multi-user communication systems.

A joint design for multi-band heterogeneous networks when deploying reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS) technique is effective to improve the capacity and coverage of various networks. However, the practical RIS has dissimilar responses to signals in different frequencies due to its structure. Therefore, directly applying existing schemes to multi-band heterogeneous networks leads to beam misalignment and performance degradation issues. This paper considers RIS-assisted multi-band heterogeneous networks where base stations (BSs) use different frequencies. We formulate the problem for maximizing the sum rate of all users (SR) in every frequency band, and aim to jointly design BSs precoding vectors and RIS parameters while taking user choices into account. Based on the closed-form relationship of phase shifts between frequencies, an iterative algorithm is proposed to solve the challenging non-convex problems. In particular, we use fractional programming to decouple the problem, and solve the subproblems with quadratic transform (QT) and genetic algorithm (GA). Simulation results show that the proposed scheme can significantly improve SR among all frequency bands, which could instruct the coexistence of multiple communication systems in future heterogeneous networks. What's more, results also prove that deploying RISs recklessly will result in a degradation of the network.

Cross-Layer Optimization for Industrial Internet of Things in NOMA-Based C-RANs

This article investigates nonorthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficiency (EE) by jointly optimizing the power allocation, analog, and digital precoding, which turns out to be an intractable nonconvex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus, the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, the joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying the Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with a hybrid precoding (HP) scheme can achieve higher spectral efficiency and EE than the traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme.

Distributed Satellite Relay Cooperative Communication with Optimized Signal Space Dimension

With the increasingly obvious trend of satellite communication and network integration, especially the emergence of inter satellite links, the interconnection between space nodes has become the development trend and inevitable requirement of future space communication. However, problems, such as long communication distance, large transmission delay and loss, limited network resources and frequent switching of transmission links, limit the ability of spatial information transmission. Firstly, based on the idea of ring planning and design, this paper uses the joint design of beamforming between nodes to design the physical layer network coding in the relay to realize the reliable transmission of information. Secondly, according to the diversity of relay signal space resources and network node information exchange, a joint design method of relay compression matrix and node precoding vector is studied, which breaks through the existing configuration constraints. In this scheme, the computational complexity is reduced by compressing and precoding the matrix to ensure reliable decoding while obtaining spatial alignment gain and degrees of freedom. Simulated and real data results demonstrate the superiority and effectiveness of the proposed method.

Energy Efficiency Maximization Precoding for Quantized Massive MIMO Systems

The use of low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) significantly benefits energy efficiency (EE) at the cost of high quantization noise for massive multiple-input multiple-output (MIMO) systems. This paper considers a precoding optimization problem for maximizing EE in quantized downlink massive MIMO systems. To this end, we jointly optimize an active antenna set, precoding vectors, and allocated power; yet acquiring such joint optimal solution is challenging. To resolve this challenge, we decompose the problem into precoding direction and power optimization problems. For precoding direction, we characterize the first-order optimality condition, which entails the effects of quantization distortion and antenna selection. We cast the derived condition as a functional eigenvalue problem, wherein finding the principal eigenvector attains the best local optimal point. To this end, we propose generalized power iteration based algorithm. To optimize precoding power for given precoding direction, we adopt a gradient descent algorithm for the EE maximization. Alternating these two methods, our algorithm identifies a joint solution of the active antenna set, the precoding direction, and allocated power. In simulations, the proposed methods provide considerable performance gains. Our results suggest that a few-bit DACs are sufficient for achieving high EE in massive MIMO systems.

Secure Transmission for Hierarchical Information Accessibility in Downlink MU-MIMO

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.

Enhancing diversity of OFDM with joint spread spectrum and subcarrier index modulations

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.