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Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (5 May 2024) | Viewed by 16026

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Special Issue Editors

Dr. Neng Ye

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Guest Editor

School of Cyberspace Science and Technology/Beijing Institute of Technology, Beijing 100081, China
Interests: UAV Communications; next-generation radio access; information theory; non-orthogonal multiple access; coding theory and machine learning
Special Issues, Collections and Topics in MDPI journals

Dr. Aihua Wang

E-Mail Website
Guest Editor

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Interests: mobile communication; signal processing

Dr. Chao Zhu

E-Mail Website
Guest Editor

School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Interests: mobile networks; edge computing

Special Issue Information

Dear Colleagues,

Future sensor networks will witness a paradigm shift towards heterogeneous devices, massive connections, and ubiquitous distributions as we progress towards 2030. Existing wireless transmission technologies suffer from restricted connectivity, expandability and spectral efficiency. There is a growing interest in technologies capable of overcoming these challenges. Non-orthogonal transmission techniques allow multiple users to share the same transmission media, providing additional degrees of freedom for efficient communication. The aforementioned requirements for future sensor networks could be fulfilled by the novel non-orthogonal physical-layer technologies (e.g., non-orthogonal multiple access, waveforms and precoding). Novel recently developed ideas have triggered the evolution of transmission technologies for future ubiquitous sensor networks. This Special Issue of Sensors aims to collect state-of-the-art research papers on topics including but not limited to non-orthogonal transmission techniques and technologies for future ubiquitous sensor communications.

Sensors are used to collect data of interest in diversified scenarios, which enable smart cities and other ubiquitous monitoring applications. This Special Issue focuses on the transmission of data collected by sensors. Since sensor networks usually operate in the unlicensed spectrum, the available wireless resources for data transmission are scarce, especially when a large number of sensor nodes are deployed. Non-orthogonal transmission technologies can effectively improve the efficiency of transmission and resource utilization, and enable simultaneous connections. This is particularly attractive for supporting the massive connectivity of future ubiquitous sensor networks.

Dr. Neng Ye
Dr. Aihua Wang
Dr. Chao Zhu
Guest Editors

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Keywords

non-orthogonal
NOMA
modulation design
non-orthogonal waveform
multi-user communication
MIMO
integrated space–air–ground network
satellite communications
machine learning
edge computing

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Published Papers (7 papers)

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Research

22 pages, 2801 KiB

Open AccessArticle

Efficient Precoding and Power Allocation Techniques for Maximizing Spectral Efficiency in Beamspace MIMO-NOMA Systems

by Yongfei Liu, Lu Si, Yuhuan Wang, Bo Zhang and Weizhang Xu

Sensors 2023, 23(18), 7996; https://doi.org/10.3390/s23187996 - 20 Sep 2023

Cited by 1 | Viewed by 1242

Abstract

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. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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18 pages, 9060 KiB

Open AccessArticle

Design and Implementation of a Highly Efficient Quasi-Cyclic Low-Density Parity-Check Transceiving System Using an Overlapping Decoder

by Yuxuan Sun, Liangbin Zhao, Jianguo Li, Ziyi Zhang, Xiao Yang and Xiangyuan Bu

Sensors 2023, 23(18), 7828; https://doi.org/10.3390/s23187828 - 12 Sep 2023

Viewed by 1127

Abstract

The traditional LDPC encoding and decoding system is characterized by low throughput and high resource consumption, making it unsuitable for use in cost-efficient, energy-saving sensor networks. Aiming to optimize coding complexity and throughput, this paper proposes a combined design of a novel LDPC code structure and the corresponding overlapping decoding strategies. With regard to structure of LDPC code, a CCSDS-like quasi-cyclic parity check matrix (PCM) with uniform distribution of submatrices is constructed to maximize overlap depth and adapt the parallel decoding. In terms of reception decoding strategies, we use a modified 2-bit Min-Sum algorithm (MSA) that achieves a coding gain of 5 dB at a bit error rate of

10^{- 6}

compared to an uncoded BPSK, further mitigating resource consumption, and which only incurs a slight loss compared to the standard MSA. Moreover, a shift-register-based memory scheduling strategy is presented to fully utilize the quasi-cyclic characteristic and shorten the read/write latency. With proper overlap scheduling, the time consumption can be reduced by one third per iteration compared to the non-overlap algorithm. Simulation and implementation results demonstrate that our decoder can achieve a throughput up to 7.76 Gbps at a frequency of 156.25 MHz operating eight iterations, with a two-thirds resource consumption saving. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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21 pages, 3702 KiB

Open AccessArticle

Deep Learning-Aided Modulation Recognition for Non-Orthogonal Signals

by Jiaqi Fan, Linna Wu, Jinbo Zhang, Junwei Dong, Zhong Wen and Zehui Zhang

Sensors 2023, 23(11), 5234; https://doi.org/10.3390/s23115234 - 31 May 2023

Cited by 1 | Viewed by 1964

Abstract

Automatic Modulation Recognition (AMR) can obtain the modulation mode of the received signal for subsequent processing without the assistance of the transmitter. Although the existing AMR methods have been mature for the orthogonal signals, these methods face challenges when deployed in non-orthogonal transmission systems due to the superimposed signals. In this paper, we aim to develop efficient AMR methods for both downlink and uplink non-orthogonal transmission signals using deep learning-based data-driven classification methodology. Specifically, for downlink non-orthogonal signals, we propose a Bi-directional Long Short-Term Memory (BiLSTM)-based AMR method that exploits long-term data dependence to automatically learn irregular signal constellation shapes. Transfer learning is further incorporated to improve recognition accuracy and robustness under varying transmission conditions. For uplink non-orthogonal signals, the combinatorial number of classification types explodes exponentially with the number of signal layers, which becomes the major obstacle to AMR. We develop a spatio-temporal fusion network based on the attention mechanism to efficiently extract spatio-temporal features, and network details are optimized according to the superposition characteristics of non-orthogonal signals. Experiments show that the proposed deep learning-based methods outperform their conventional counterparts in both downlink and uplink non-orthogonal systems. In a typical uplink scenario with three non-orthogonal signal layers, the recognition accuracy can approach

96.6 %

in the Gaussian channel, which is

19 %

higher than the vanilla Convolution Neural Network. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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19 pages, 4870 KiB

Open AccessArticle

FDSS-Based DFT-s-OFDM for 6G Wireless Sensing

by Lu Chen, Jianxiong Pan, Jing Zhang, Junfeng Cheng, Luyan Xu and Neng Ye

Sensors 2023, 23(3), 1495; https://doi.org/10.3390/s23031495 - 29 Jan 2023

Cited by 1 | Viewed by 4170

Abstract

Integrated sensing and communications (ISAC) is emerging as a key technology of 6G. Owing to the low peak-to-average power ratio (PAPR) property, discrete Fourier transform spread orthogonal frequency-division multiplexing (DFT-s-OFDM) is helpful to improve the sensing range and suitable for high-frequency transmission. However, compared to orthogonal frequency-division multiplexing (OFDM), the sensing accuracy of DFT-s-OFDM is relatively poor. In this paper, frequency-domain spectral shaping (FDSS) is adopted to enhance the performances of DFT-s-OFDM including sensing accuracy and PAPR by adjusting the correlation of signals. Specifically, we first establish a signal model for the ISAC system, followed by the description of performance indicators. Then, we analyze the influence of amplitude fluctuation of frequency domain signals on sensing performance, which shows the design idea of FDSS-enhanced DFT-s-OFDM. Further, a FDSS-enhanced DFT-s-OFDM framework is introduced for ISAC, where two types of FDSS filters including a pre-equalization filter and an isotropic orthogonal transform algorithm (IOTA) filter are designed. The simulation results show that the proposed scheme can obtain about 4 dB performance gain in terms of sensing accuracy over DFT-s-OFDM. In addition, FDSS-enhanced DFT-s-OFDM can significantly reduce PAPR and improve the power amplifier efficiency. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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19 pages, 668 KiB

Open AccessArticle

Resource Allocation in Multi-Carrier Multiplexed NOMA Cooperative System

by Jie Zeng, Jiaying Sun, Yuxin Song, Jiajia Mei, Tiejun Lv and Shidong Zhou

Sensors 2022, 22(16), 6023; https://doi.org/10.3390/s22166023 - 12 Aug 2022

Cited by 1 | Viewed by 1541

Abstract

Non-orthogonal multiple access (NOMA) cooperative communication technology can combine the advantages of NOMA and cooperative communication, providing high spectrum efficiency and increasing user coverage for next-generation wireless systems. However, the research on NOMA cooperative communication technology is still in a preliminary stage and has mainly concentrated on the scenario of fewer users. This paper focuses on a user-centered NOMA collaboration system in an ultra-dense network, and it constructs a resource allocation optimization problem to meet the demands of each user. Then, this paper decomposes the optimization problem into two subproblems; one is the grouping match among multiple relays and users, and the other is jointly allocating power and subcarrier resources. Accordingly, a dynamic packet matching algorithm based on Gale–Shapley and an iterative algorithm based on the difference of convex functions programing are proposed. Compared with existing schemes, the proposed algorithms can improve system throughput while ensuring the quality of service of users. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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25 pages, 1825 KiB

Open AccessArticle

Guaranteeing QoS for NOMA-Enabled URLLC Based on κ–μ Shadowed Fading Model

by Jie Zeng, Yuxin Song, Teng Wu, Tiejun Lv and Shidong Zhou

Sensors 2022, 22(14), 5279; https://doi.org/10.3390/s22145279 - 14 Jul 2022

Cited by 3 | Viewed by 1814

Abstract

Sixth-generation (6G) wireless communication scenarios are complex and diverse. Small-scale fading is a key part of wireless channels and its impact on performance in scenarios with time sensitivity and 6G ultrareliable and low latency communications (URLLC) quality-of-service requirements cannot be ignored. Therefore, it is necessary to accurately characterize small-scale fading when designing wireless communication systems. In this paper, we derive approximate closed form expressions for the probability density function, cumulative distribution function and moment-generating function of the postprocessing signal-to-noise ratio following the zero-forcing detector in a cell-free massive multiple-input multiple-output (CF mMIMO) system. CF mMIMO system is a nonorthogonal multiple access (NOMA) system that enables users to share all channel uses and can ensure the fairness of the communication quality experienced by different users. Our key contributions include the extension of the

κ

–

μ

shadowed fading model to a CF mMIMO system and the proposal of theoretical tools (the derived closed-form expression) to improve its mathematical tractability. By exploiting the statistical characterizations of the arrival and service processes, another important contribution is the exploitation of the upper bound of the queuing delay violation probability (UB-QDVP) over the Mellin transforms of the arrival and service processes in the proposed CF mMIMO system under the

κ

–

μ

shadowed fading model. Corroborated by extensive simulations, our analyses validate that the CF mMIMO system outperforms the orthogonal multiple access and power-domain NOMA systems and reveal the relationships among different small-scale fading types, energy efficiency, delay and the UB-QDVP, as well as the accuracy and effectiveness of the proposed theoretical tools based on the

κ

–

μ

shadowed fading model. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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18 pages, 1769 KiB

Open AccessArticle

Enhancing PAPR and Throughput for DFT-s-OFDM System Using FTN and IOTA Filtering

by Xinran Zhuo, Jianxiong Pan, Huwei Wang, Xiangming Li and Neng Ye

Sensors 2022, 22(13), 4907; https://doi.org/10.3390/s22134907 - 29 Jun 2022

Viewed by 2832

Abstract

High frequency wireless communication aims to provide ultra high-speed transmissions for various application scenarios. The waveform design for high frequency communication is challenging due to the requirements for high spectrum efficiency, as well as good hardware compatibility. With high flexibility and low peak-to-average power ratio (PAPR), discrete Fourier transformation spreading-based orthogonal frequency division multiplexing (DFT-s-OFDM) can be a promising candidate waveform. To further enhance the spectral efficiency, we integrate faster-than-Nyquist (FTN) signaling in DFT-s-OFDM, and find that the PAPR performance can also be improved. While FTN can introduce increased inter-symbol interference (ISI), in this paper, we deploy an isotropic orthogonal transform algorithm (IOTA) filter for FTN-enhanced DFT-s-OFDM, where the compact time-frequency structure of the IOTA filter can significantly reduce the ISI. Simulation results show that the proposed waveform is capable of achieving good performance in PAPR, bit error rate (BER) and throughput, simultaneously, with

3.5

dB gain in PAPR and 50% gain in throughput. Full article

(This article belongs to the Special Issue Non-orthogonal Transmission Technologies for Ubiquitous Sensor Networks)

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