Novel Power-Imbalanced Dense Codebooks for Reliable Multiplexing in Nakagami Channels

This paper studies enhanced dense code multiple access (DCMA) system design for downlink transmission over the Nakagami-m fading channels. By studying the DCMA pairwise error probability (PEP) in a Nakagami-m channel, a novel design metric called minimum logarithmic sum distance (MLSD) is first derived. With respect to the proposed MLSD, we introduce a new family of power-imbalanced dense codebooks by deleting certain rows of a special non-unimodular circulant matrix. Simulation results demonstrate that our proposed dense codebooks lead to both larger minimum Euclidean distance and MLSD, thus yielding significant improvements of error performance over the existing sparse code multiple access and conventional unimodular DCMA schemes in Nakagami-m fading channels under different overloading factors

Design of Power-Imbalanced SCMA Codebook

Sparse code multiple access (SCMA) is a promising multiuser communication technique for the enabling of future massive machine-type networks. Unlike existing codebook design schemes assuming uniform power allocation, we present a novel class of SCMA codebooks which display power imbalance among different users for downlink transmission. Based on the Star-QAM mother constellation structure and with the aid of genetic algorithm, we optimize the minimum Euclidean distance (MED) and the minimum product distance (MPD) of the proposed codebooks. Numerical simulation results show that our proposed codebooks lead to significantly improved error rate performances over Gaussian channels and Rayleigh fading channels

Wild Animal Information Collection Based on Depthwise Separable Convolution in Software Defined IoT Networks

The wild animal information collection based on the wireless sensor network (WSN) has an enormous number of applications, as demonstrated in the literature. Yet, it has many problems, such as low information density and high energy consumption ratio. The traditional Internet of Things (IoT) system has characteristics of limited resources and task specificity. Therefore, we introduce an improved deep neural network (DNN) structure to solve task specificity. In addition, we determine a programmability idea of software-defined network (SDN) to solve the problems of high energy consumption ratio and low information density brought about by low autonomy of equipment. By introducing some advanced network structures, such as attention mechanism, residuals, depthwise (DW) convolution, pointwise (PW) convolution, spatial pyramid pooling (SPP), and feature pyramid networks (FPN), a lightweight object detection network with a fast response is designed. Meanwhile, the concept of control plane and data plane in SDN is introduced, and nodes are divided into different types to facilitate intelligent wake-up, thereby realizing high-precision detection and high information density of the detection system. The results show that the proposed scheme can improve the detection response speed and reduce the model parameters while ensuring detection accuracy in the software-defined IoT networks

Design of Power-Imbalanced SCMA Codebook

Sparse code multiple access (SCMA) is a promising multiuser communication technique for the enabling of future massive machine-type networks. Unlike existing codebook design schemes assuming uniform power allocation, we present a novel class of SCMA codebooks which display power imbalance among different users for downlink transmission. Based on the Star-QAM mother constellation structure and with the aid of genetic algorithm, we optimize the minimum Euclidean distance (MED) and the minimum product distance (MPD) of the proposed codebooks. Numerical simulation results show that our proposed codebooks lead to significantly improved error rate performances over Gaussian channels and Rayleigh fading channels

Uniform-Distributed Constellation Codebook Design for High-Capacity Visible Light Communications

This letter studies high-capacity visible light communication (VLC) based on code-domain non-orthogonal multiple access (CD-NOMA) with the goal of enabling the future machinetype communication networks. To fulfill the non-negative signal constraint and mitigate/suppress the nonlinear effects and shot noise, a novel uniform-distributed constellation codebook is developed for lower peak power and larger minimum Euclidean distance (MED). The simulation results demonstrate that our proposed codebooks give rise to significantly improved error rate performance compared to existing codebooks. In addition, codebooks with larger overloading factors are presented to achieve high-capacity communication

Sparse Code Multiple Access for 6G Wireless Communication Networks: Recent Advances and Future Directions

As 5G networks are being rolled out in many different countries nowadays, the time has come to investigate how to upgrade and expand them toward 6G, where the latter is expected to realize the interconnection of everything as well as the development of a ubiquitous intelligent mobile world for intelligent life. To enable this epic leap in communications, this article provides an overview and outlook on the application of sparse code multiple access (SCMA) for 6G wireless communication systems, which is an emerging disruptive non-orthogonal multiple access (NOMA) scheme for the enabling of massive connectivity. We propose to apply SCMA to a massively distributed access system whose architecture is based on fiber-based visible light communication, ultra-dense networks, and NOMA. Under this framework, we consider the interactions between optical fronthauls and wireless access links. In order to stimulate more upcoming research in this area, we outline a number of promising directions associated with SCMA for faster, more reliable, and more efficient multiple access in future 6G communication networks