Codebook Design Method Research Articles

Interleaving based SCMA Codebook Design Using Arnold’s Cat Chaotic Map

Non-orthogonal multiple access (NOMA) technology is a significant topic of the present 5G investigation. A possible NOMA approach is Sparse Code Multiple Access (SCMA), increasing next-generation communication's ability to handle multiple users. In SCMA, codebook designing and optimization are crucial components that define the performance of multiple access systems. In this work, the complete design procedure of the SCMA codebook based on interleaving is explained and simulated. Furthermore, a chaotic interleaving based onArnold’sCat map is proposed to reduce the computational complexity. The performance of the SCMA codebook based on interleaving is evaluated through comparison with selected codebooks for SCMA multiplexing. The measures used for performance evaluation include Bit Error rate (BER), Peak to Average Power Ratio(PAPR), and minimum EuclidianDistance(MED). The results show that the proposed codebook with chaotic interleaving achieves comparable performance to the traditional codebook based on interleaving and less MED and higher BER compared to computer-generated and 16-star QAM codebook design methods but with reduced complexity.

Energy Efficient Beamforming for Millimeter-Wave Massive MIMO Systems Under User-Wise Asymmetric Uplink–Downlink Traffic

In this paper, a beamforming scheme that aims to support user-wise asymmetric uplink-downlink (UL-DL) traffic in a more energy-efficient manner is proposed for time-division duplex (TDD) millimeter-wave massive multiple-input-multiple-output (MIMO) systems. Assuming that proper data links have been established during the initial access stage for DL or UL traffic, we consider the beamforming problem for UL or DL whose payload traffic is much lighter than the other link. Such asymmetric traffic allows part of the massive MIMO array to be deactivated in order to achieve a higher energy efficiency (EE) while still meeting the spectrum efficiency (SE) requirements for UL or DL. To deal with such a problem, we propose the corresponding phase shifter (PS) deactivation strategies based on different SE constraints for individual mobile stations or users independently, which select the PSs to be deactivated accordingly with low computational complexity. We then propose a novel codebook design method, which relies on the iteratively updated average main beam gain, in order to pursue a flatter beam under asymmetric DL-UL traffic that interacts with the corresponding PS deactivation strategy. The proposed codebook not only offers flexible beam width and flat main beam gain, but also can generate some good candidate codewords to account for the need of beam refinements, after some of the PSs have been deactivated. Simulation results demonstrated the superiority of the proposed energy efficient PS deactivation approach and the corresponding codebook design.

Multiple Access for Near-Field Communications: SDMA or LDMA?

Spatial division multiple access (SDMA) is essential to improve the spectrum efficiency for multi-user multiple-input multiple-output (MIMO) communications. The classical SDMA for massive MIMO with hybrid precoding heavily relies on the angular orthogonality in the far field to distinguish multiple users at different angles, which fails to fully exploit spatial resources in the distance domain. With the dramatically increasing number of antennas, the extremely large-scale antenna array (ELAA) introduces additional resolution in the distance domain in the near field. In this paper, we propose the concept of location division multiple access (LDMA) to provide a new possibility to enhance spectrum efficiency compared with classical SDMA. The key idea is to exploit extra spatial resources in the distance domain to serve different users at different locations (determined by angles and distances) in the near field. Specifically, the asymptotic orthogonality of near-field beam focusing vectors in the distance domain is proved, which reveals that near-field beam focusing is able to focus signals on specific locations with limited leakage energy at other locations. This special property could be leveraged in hybrid precoding to mitigate inter-user interferences for spectrum efficiency enhancement. Moreover, we provide the spherical-domain codebook design method for LDMA communications with the uniform planar array, which provides the sampling method in the distance domain. Additionally, performance analysis of LDMA is provided to reveal that the asymptotic optimal spectrum efficiency could be achieved with the increasing number of antennas. Finally, simulation results verify the superiority of the proposed LDMA over SDMA in different scenarios.

Computer Vision Aided Codebook Design for MIMO Communications Systems

MmWave communications systems usually rely on analog or hybrid analog/digital architectures and thus need a predefined codebook to perform beamforming. Traditional codebooks are designed for universal environments, although in practice a particular BS will only serve a particular environment. In this paper, we propose novel site-specific codebook design methods by utilizing the visual information captured through cameras. Different from other site-specific codebook design methods that require a large amount of measured channel state information (CSI), the proposed ones need only a simple snapshot of the environment followed by efficient computer vision (CV) techniques. Thus the proposed CV-aided codebook design reduces the overhead of communications system, such as the cost of time, human resources, as well as the hardware installation and calibration. Specifically, we propose a CV-based approach that detects the LOS area around the BS and reconstructs the LOS channel vectors set (CVS).With this knowledge, we build a vision-based beam codebook using Lloyd algorithm. Further, we design a FusionNet to generate the codebook that can serve the non-line-of-sight (NLOS) users. The simulation results demonstrate the effectiveness of the proposed CV-aided codebook design methods and their superiority compared to the conventional methods.

Convolutional neural network and clustering-based codebook design method for massive MIMO systems

In this paper, we propose a convolutional neural network (CNN) and clustering-based codebook design method. Specifically, we train two different CNNs, i.e., CNN1 and CNN2, to compress the channel state information (CSI) matrices into the channel vectors and recover the channel vectors back into the CSI matrices, respectively. After that, the clustering algorithm clusters the output of CNN1, i.e., the channel vectors into several clusters and outputs a centroid for each cluster. The sum distance between each centroid and the channel vectors in the corresponding cluster is the smallest, which can lead to the maximum sum rate of massive MIMO codebook design. Then, the centroids are recovered into matrices by CNN2. The output of CNN2 is our proposed codebook for massive multiple-input multiple-output (MIMO) systems. In the simulation, we compare the performance of different clustering algorithms. We also compare the proposed codebook with the traditional discrete Fourier transform (DFT) codebook. Simulation results show the superiority of the proposed algorithm.

Deep Learning-Based Codebook Designs for Generalized Space Shift Keying Systems

In this paper, we propose a novel deep learning (DL)-based codebook design method for generalized space shift keying (GSSK) systems. In this DL-based method, the transmitter and receiver of GSSK systems are designed based on deep neural network (DNN). By training the DNN in an end-to-end manner, the DL-based method can adaptively generate suitable binary codewords and combine them into a codebook for GSSK systems. Simulation results show that the proposed DL-based method obtains better performance compared to conventional approaches.

A review of codebook design methods for sparse code multiple access

<span lang="EN-GB">The progressions in telecommunication beyond the 5<sup>th</sup> generation have created a need to improve research drifts. The current 5G study has an important focus on non-orthogonal multiple access (NOMA) technology. sparse code multiple access (SCMA) is a promising technique within NOMA, enhancing the multi-user handling capability of next-generation communication. In the SCMA sphere, codebook designing and optimisation are essential research matters. This study conversed with different codebook design practises existing in the literature, analysing them for numerous parameters, including bit error rate (BER), an optimisation technique, and channel settings. From the analysis, the paper presents the efficiency of different approaches. The article also discusses the prospects and challenges of SCMA optimisation in practical implementation in various domains.</span>

A Multistage Method for SCMA Codebook Design Based on MDS Codes

Sparse Code Multiple Access (SCMA) has been recently proposed for the future generation of wireless communication standards. SCMA system design involves specifying several parameters. In order to simplify the procedure, most works consider a multistage design approach. Two main stages are usually emphasized in these methods: sparse signatures design (equivalently, resource allocation) and codebook design. In this paper, we present a novel SCMA codebook design method. The proposed method considers SCMA codebooks structured with an underlying vector space obtained from classical block codes. In particular, when using maximum distance separable (MDS) codes, our proposed design provides maximum signal-space diversity with a relatively small alphabet. The use of small alphabets also helps to maintain desired properties in the codebooks, such as low peak-to-average power ratio and low-complexity detection.

An Efficient Large Resource-User Scale SCMA Codebook Design Method

Sparse code multiple access (SCMA) is an attractive non-orthogonal multiple access (NOMA) technology. An effective SCMA codebook design metrics is maximizing minimum Euclidean distance between superimposed codewords. However, the number of superimposed codewords will significantly expand with the growing number of resources and users, making the max–min problem impractical. To this end, an efficient suboptimal SCMA codebook design method is proposed for large source-user scale. We first project multi-dimensional superimposed codewords to resources to reduce the number of superimposed codewords in the constellation. Then we formulate the max–min optimization as a nonconvex quadratically constrained quadratic programming (QCQP) problem and solve it by semidefinite relaxation (SDR). Simulation result shows that the method, which can dramatically reduce computational complexity, is able to solve large-scale codebook design problem while incurring little loss in performance compared with the existing codebook design method.

Beam Training Based on Dynamic Hierarchical Codebook for Millimeter Wave Massive MIMO

Beam training based on hierarchical codebook for millimeter wave (mmWave) massive MIMO is investigated. Unlike the existing work using the same hierarchical codebook to estimate different multi-path components (MPCs), dynamic hierarchical codebooks which are updated according to the estimated MPCs are adopted. First, a generalized hierarchical codebook design method is proposed. Then based on this method, a beam training method which dynamically updates the hierarchical codebook by removing the contribution of the estimated MPCs from the codebook is proposed. Simulation results verify the effectiveness of our method and show that the proposed method outperforms the existing ones in terms of the success detection rate of beam training.

An Efficient SCMA Codebook Design Based on Lattice Theory for Information-Centric IoT

Different from traditional communication systems, information-centric Internet of things (IC-IoT) as a novel smart paradigm needs to guarantee end-to-end connectivity for rapidly growing smart devices. How to meet the demands of massive connection has become a key problem for IC-IoT. Sparse code multiple access (SCMA) as a code-domain non-orthogonal multiple access (NOMA) technique has been intensively investigated. With SCMA, each user employs different sub-carrier frequencies for transmission, and different users can share the same sub-carrier frequency via superposition coding. The spectrum efficiency is thus improved. However, designing large-scale codebook sets is still an open problem for SCMA. In this paper, a new lattice-based codebook design method is proposed via mother constellation optimization. First, the optimization problem of the mother constellation is formulated. Through analysis, the problem can be converted into two sub-problems. Accordingly, we first use the lattice theory to find a constellation containing infinite points with large coding gain. After that, we search for a boundary that contains a set of points via spherical packing. Such an approach enables us to obtain a real constellation satisfying a power saving criterion. Secondly, the mother constellation with large power variance is obtained from the real multi-dimensional constellation. Finally, lattice-based codebooks are generated by combining the mother constellation and the mapping matrices with constellation rotation. Simulations demonstrate that the designed codebooks have improved bit error rate (BER) performance with large codebook size, especially at high signal to noise ratio (SNR).

Design and Analysis of SCMA Codebook Based on Star-QAM Signaling Constellations

In this paper, a novel codebook design method for sparse code multiple access (SCMA) is proposed and an analytical framework to evaluate the bit error rate (BER) performance is developed. In particular, to meet the codebook design criteria based on the pairwise error probability, a novel codebook with large minimum Euclidean distance employing the star quadrature amplitude modulation signal constellations is designed. In addition, with the aid of the phase distribution of the presented SCMA constellations, BER of SCMA system over downlink Rayleigh fading channel is obtained in closed-form expression. The simulation and analytical results show that the presented SCMA codebook outperforms the existing codebooks and low-density signature, and the proposed design is more efficient for the SCMA codebook with large size and/or high dimension. Moreover, the derived theoretical BER results match well the simulation results, especially in the high signal-to-noise ratio regimes.

Fast codebook design method for image vector quantisation

Vector quantisation (VQ) is a widely used method for data compression or data clustering. This study proposes a fast codebook design method for image VQ. General particle swarm optimisation (PSO)- K -means hybrid methods for codebook design take too much time. To deal with this problem, the authors present a new clustering method, which takes a very short time and generates a pretty good codebook. This method contains four parts, i.e. pooling, PSO algorithm, reverse cast, and K -means algorithm. Pooled images are used for the PSO process while original images are used for K -means fine-tuning, and these two processes connected by the reverse cast process. In the authors' experiment, this method can dramatically reduce the computation time by using big sizes of pooling window or enhance the codebook quality by using small sizes of pooling window. They can make the calculation time almost one-tenth of that of the PSO- K -means hybrid method, and the scheme is also faster than the K -means algorithm. Experimental results demonstrate that the main advantages of the proposed algorithm lie in the fact that it can reduce the computation time and enhance the quality of codebooks.

A general codebook design method for vector quantization

Vector quantization (VQ) is widely used in image processing applications, the primary focus of VQ is to determine a codebook to represent the original image well. In order to make a codebook perform better on both distortion and bit rate (BR), a general codebook (GCB) for VQ is proposed in this paper. Unlike common codebook (CCB) or private codebook (PCB), GCB is a new structure of codebook where the codewords can either come from CCB or by training the input image. By applying the codewords in CCB that perform well and updating inactive codewords, only the new generated codewords and flags of codewords to be replaced are transmitted along with index table (IT). Therefore,the BR can be significantly reduced while the performance of distortion can be efficiently improved. The experimental results demonstrate that our proposed GCB has a better performance than CCB and various kinds of PCB-based methods.

Signal Shaping and Precoding for MIMO Systems Using Lattice Codes

In this paper, we study the max–min Euclidean distance-based multiple-input multiple-output (MIMO) transmit codebook design with channel state information at transmitter. Different from existing max–min precoder designs, a shaping-based codebook design method is proposed to construct the codebook from a structured signal lattice. Hyperrectangle shaping is found to be superior to the shaping region of the precoder-based design in terms of power efficiency. Based on the proposed hyper-rectangle shaping region, the number of available spatial dimensions used for codebook construction is first determined through maximizing the approximated constellation figure of merit. Then, the codebook is derived by lattice precoding and shifting the unshaped latticed points inside the hyperrectangle region. Numerical results illustrate that our proposed shaping-based codebook is strictly better than present precoder-based codebook designs and is more robust under different MIMO channel conditions.

High‐quality initial codebook design method of vector quantisation using grouping strategy

The codebook design which determines the quality of the encoded images is an important problem in the vector quantisation technique. The Linde–Buzo–Gray (LBG) technique is a widely used algorithm in the codebook design. However, LBG algorithm is very sensitive to the initial codebook and tends to trap to the local minimum. In this study, a high-quality initial codebook design method is proposed. The proposed method utilises both the mean characteristic value and variance characteristic value of training vectors to divide the training vectors into groups. Then codewords are selected from each group to generate an initial codebook. The experimental results demonstrate that the authors proposed method has a better performance in the initial codebook than that of the related methods.

Codebook Design Method Based on Minimax Optimization for Data Transmission over WCDMA Voice Channel

본 논문에서는 음성 채널을 통해 데이터를 전송하기 위한 데이터 모뎀의 코드북 설계 방법에 대해 기술하였다. 제안한 코드북 설계 방법은 minimax 최적화 기법을 이용하여 탐색 공간에 분포하는 심볼들 중 최대 중첩을 갖는 심볼들의 중첩을 최소화하도록 하는 방법이다. 제안한 방법에 따라 설계된 코드북을 적용한 데이터 전송 시스템을 제시하였으며, 모의 실험과 실제 이동통신망 적용 실험을 통해 제안한 방법의 성능을 평가하였다. In this paper, a novel codebook design method for data modem over voice channel is presented. Proposed method searches the symbols which have the maximum probability distribution overlap in the symbol space and minimizes the overlap to improve the symbol error rate via minimax optimization. We present numerical simulations and an example implementation. We also give the results of the experiment tests.

Performance analysis of MIMO beamforming with imperfect feedback

SUMMARYThe quality of channel state information at the transmitter (CSIT) is critical to MIMO beamforming systems. However, in practical wireless systems, CSIT suffers from imperfections originating from quantization effects, feedback error and feedback delay. In this paper, we study the impact of feedback error and delay on the symbol error rate of MIMO beamforming systems with finite rate feedback. The feedback channel is modeled as a uniform symmetric channel. We derive an symbol error rate upper bound that is tight for a good beamformer. We also quantify the diversity gain and array gain loss due to the feedback error and delay. The codebook design method that is applicable to the beamforming systems with error or delay feedback is discussed. Both analytical and simulation results show that feedback error and delay will make the system behave badly at high signal‐to‐noise ratios. Copyright © 2012 John Wiley & Sons, Ltd.

Enhanced closed-loop EOSTBC schemes for multiple transmit antennas

In this paper, a novel closed-loop multiple antennas transmission scheme suitable for M = 2p(p ⩾2) transmit antennas is proposed on the basis of the extended orthogonal space–time block codes. And, all 2p transmit antennas are divided into p groups, and each group includes two antennas, and Alamouti orthogonal space-time block code is adopted. All p groups are used to transmit the same source symbols, and each group is scaled by one scale matrix before transmission. The elegantly designed scale matrix takes both power allocation and phase rotation into account to optimise the antenna array gain and exploit full transmit diversity while maintaining low linear decoding complexity provided by Alamouti code. By formulating the problem as a convex optimisation problem, the optimal solution for the scale matrix is achieved. In addition, several practical feedback codebook design methods are proposed, and their advantages over the existing closed-loop extended orthogonal space–time block code schemes are clearly demonstrated by both analysis and simulation results. Copyright © 2012 John Wiley & Sons, Ltd.

Fast codebook design of vector quantisation

To reduce the computational overhead of the codebook design of vector quantisation, a fast codebook design method is proposed. In this method, the energy distribution of vectors is improved by rearranging the elements of vectors based on the information of the energy distribution at each dimension of the initial codebook. Then using the subvectors and their characteristic values, a three-step elimination criterion is introduced to efficiently reduce computational overheads. Experimental results demonstrate the effectiveness of the proposed method in terms of arithmetical operations and search space.