A Survey on Transmission Schemes on Large-Scale Internet of Things with Nonorthogonal Multiple Access

This paper performs a comprehensive survey on transmission schemes for the large-scale Internet of things (IoT) networks with nonorthogonal multiple access (NOMA). By solving the interference among users, NOMA can significantly improve the frequency reuse efficiency and support multiple users to use the same frequency resources. It is considered to be one of the most effective technologies for the next-generation wireless communication. However, there are still many challenges on the transmission schemes for the large-scale NOMA system, including the short-data packet transmission, active user detection, channel estimation, and data detection. In order to meet these challenges, this paper first reviews the short-packet transmission in the large-scale NOMA systems and then reviews the active user detection and channel estimation technologies of the considered systems.

[1]  Liseng Fan,et al.  Intelligent ubiquitous computing for future UAV-enabled MEC network systems , 2021, Cluster Computing.

[2]  Tao Zhang,et al.  Special Section on Telematics Advances for Vehicular Communication Networks , 2012, IEEE Trans. Veh. Technol..

[3]  Fasheng Zhou,et al.  Intelligent secure mobile edge computing for beyond 5G wireless networks , 2021, Phys. Commun..

[4]  Caijun Zhong,et al.  Statistical CSI based design for intelligent reflecting surface assisted MISO systems , 2020, Science China Information Sciences.

[5]  George K. Karagiannidis,et al.  Learning-Based Signal Detection for MIMO Systems With Unknown Noise Statistics , 2021, IEEE Transactions on Communications.

[6]  Junjuan Xia,et al.  Battery-constrained Federated Edge Learning in UAV-enabled IoT for B5G/6G Networks , 2021, Phys. Commun..

[7]  Guodong Zhao,et al.  Primary Channel Gain Estimation for Spectrum Sharing in Cognitive Radio Networks , 2016, IEEE Transactions on Communications.

[8]  Rui Zhao,et al.  Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things , 2020, Phys. Commun..

[9]  Octavia A. Dobre,et al.  Hardware Impaired Ambient Backscatter NOMA Systems: Reliability and Security , 2020, IEEE Transactions on Communications.

[10]  Yi Qian,et al.  Energy-efficient design for mmWave-enabled NOMA-UAV networks , 2021, Science China Information Sciences.

[11]  Lisheng Fan,et al.  Efficient and flexible management for industrial Internet of Things: A federated learning approach , 2021, Comput. Networks.

[12]  Victor C. M. Leung,et al.  Optimization or Alignment: Secure Primary Transmission Assisted by Secondary Networks , 2018, IEEE Journal on Selected Areas in Communications.

[13]  Pingzhi Fan,et al.  Active user and data detection for uplink grant-free NOMA systems , 2020, China Communications.

[14]  Arumugam Nallanathan,et al.  Dilated Convolution Based CSI Feedback Compression for Massive MIMO Systems , 2021, IEEE Transactions on Vehicular Technology.

[15]  George K. Karagiannidis,et al.  Secure Cache-Aided Multi-Relay Networks in the Presence of Multiple Eavesdroppers , 2019, IEEE Transactions on Communications.

[16]  George K. Karagiannidis,et al.  Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems , 2021 .

[17]  Chun-Xia Zhang,et al.  Security-Enhanced User Pairing for MISO-NOMA Downlink Transmission , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[18]  Fumiyuki Adachi,et al.  CV-3DCNN: Complex-Valued Deep Learning for CSI Prediction in FDD Massive MIMO Systems , 2021, IEEE Wireless Communications Letters.

[19]  Hongwen Yang,et al.  A Low-Complexity Joint User Activity, Channel and Data Estimation for Grant-Free Massive MIMO Systems , 2020, IEEE Signal Processing Letters.

[20]  Anrun Li.  Enhancing the Physical Layer Security of Cooperative NOMA System , 2019, 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC).

[21]  Zhaoming Lu,et al.  Emergency Semantic Feature Vector Extraction From WiFi Signals for In-Home Monitoring of Elderly , 2021, IEEE Journal of Selected Topics in Signal Processing.

[22]  George K. Karagiannidis,et al.  Dynamic Offloading for Multiuser Muti-CAP MEC Networks: A Deep Reinforcement Learning Approach , 2021, IEEE Transactions on Vehicular Technology.

[23]  Claude E. Shannon,et al.  A mathematical theory of communication , 1948, MOCO.

[24]  Marco Di Renzo,et al.  Stochastic Geometry Modeling and System-Level Analysis of Uplink Heterogeneous Cellular Networks With Multi-Antenna Base Stations , 2016, IEEE Transactions on Communications.

[25]  Zhi Chen,et al.  Joint Channel Estimation and Multiuser Detection for Uplink Grant-Free NOMA , 2018, IEEE Wireless Communications Letters.

[26]  Xiaohu You,et al.  Generalized Channel Estimation and User Detection for Massive Connectivity With Mixed-ADC Massive MIMO , 2019, IEEE Transactions on Wireless Communications.

[27]  Lihua Li,et al.  Cooperative Wireless-Powered NOMA Relaying for B5G IoT Networks With Hardware Impairments and Channel Estimation Errors , 2020, IEEE Internet of Things Journal.

[28]  Jie Yang,et al.  Flight Delay Prediction Based on Aviation Big Data and Machine Learning , 2020, IEEE Transactions on Vehicular Technology.

[29]  Chao Shen,et al.  Latency Constrained Non-Orthogonal Packets Scheduling With Finite Blocklength Codes , 2020, IEEE Transactions on Vehicular Technology.

[30]  Qiuping Li,et al.  Edge Caching and Computation Management for Real-Time Internet of Vehicles: An Online and Distributed Approach , 2021, IEEE Transactions on Intelligent Transportation Systems.

[31]  Caijun Zhong,et al.  Location Information Aided Multiple Intelligent Reflecting Surface Systems , 2020, IEEE Transactions on Communications.

[32]  Liang Yang,et al.  On the Performance of RIS-Assisted Dual-Hop UAV Communication Systems , 2020, IEEE Transactions on Vehicular Technology.

[33]  Zhenyu Na,et al.  UAV-Supported Clustered NOMA for 6G-Enabled Internet of Things: Trajectory Planning and Resource Allocation , 2021, IEEE Internet of Things Journal.

[34]  Kaishun Wu,et al.  Physical-Layer Security of NOMA Systems Under Untrusted Users , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[35]  Caijun Zhong,et al.  Programmable Metasurface-Based Multicast Systems: Design and Analysis , 2020, IEEE Journal on Selected Areas in Communications.

[36]  Jianhua Yang,et al.  An Embedding Cost Learning Framework Using GAN , 2020, IEEE Transactions on Information Forensics and Security.

[37]  Dan Deng,et al.  A Note on Implementation Methodologies of Deep Learning-Based Signal Detection for Conventional MIMO Transmitters , 2020, IEEE Transactions on Broadcasting.

[38]  Antonios Tsourdos,et al.  Power Control Optimization for Large-Scale Multi-Antenna Systems , 2020, IEEE Transactions on Wireless Communications.

[39]  Nei Kato,et al.  6G: Opening New Horizons for Integration of Comfort, Security, and Intelligence , 2020, IEEE Wireless Communications.

[40]  George K. Karagiannidis,et al.  System Optimization of Federated Learning Networks with A Constrained Latency , 2021, IEEE Transactions on Vehicular Technology.

[41]  Fusheng Zhu,et al.  An adaptive deep learning-based UAV receiver design for coded MIMO with correlated noise , 2021, Phys. Commun..

[42]  Zhiguo Ding,et al.  I/Q Imbalance Aware Nonlinear Wireless-Powered Relaying of B5G Networks: Security and Reliability Analysis , 2020, IEEE Transactions on Network Science and Engineering.

[43]  Lihua Yang,et al.  Multiband Cooperation for 5G HetNets: A Promising Network Paradigm , 2019, IEEE Vehicular Technology Magazine.

[44]  Koji Ishibashi,et al.  Grant-Free Non-Orthogonal Multiple Access With Multiple-Antenna Base Station and Its Efficient Receiver Design , 2019, IEEE Access.

[45]  Shi Jin,et al.  Bayesian Optimal Data Detector for Hybrid mmWave MIMO-OFDM Systems With Low-Resolution ADCs , 2018, IEEE Journal of Selected Topics in Signal Processing.

[46]  Hai Lin,et al.  Spatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems , 2017, IEEE Transactions on Signal Processing.

[47]  Dong Li,et al.  Ultra-reliable MU-MIMO detector based on deep learning for 5G/B5G-enabled IoT , 2020, Phys. Commun..

[48]  George L. Turin,et al.  A statistical model of urban multipath propagation , 1972 .

[49]  George K. Karagiannidis,et al.  Secure Mobile Edge Computing Networks in the Presence of Multiple Eavesdroppers , 2022, IEEE Transactions on Communications.

[50]  Lihua Li,et al.  Secrecy Analysis of Ambient Backscatter NOMA Systems Under I/Q Imbalance , 2020, IEEE Transactions on Vehicular Technology.

[51]  Linglong Dai,et al.  Dynamic Compressive Sensing-Based Multi-User Detection for Uplink Grant-Free NOMA , 2016, IEEE Communications Letters.

[52]  Xiaojun Yuan,et al.  Sparsity Learning-Based Multiuser Detection in Grant-Free Massive-Device Multiple Access , 2018, IEEE Transactions on Wireless Communications.