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Multi-Antenna Techniques for 5G and beyond 5G Communications
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Multi-Antenna Techniques for 5G and beyond 5G Communications

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

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 19697

Special Issue Editors

Dr. Jun-Pyo Hong

E-Mail Website
Guest Editor
Department of Information and Communications Engineering, Pukyong National University, Busan 48513, Republic of Korea
Interests: caching strategies for wireless video streaming; machine learning in wireless communication systems; compressed sensing in wireless communications; cognitive radio; physical layer security; 5G mobile systems
Special Issues, Collections and Topics in MDPI journals
Dr. Jaeyoung Song

E-Mail Website
Guest Editor
Communication systems department, EURECOM, 06904 Biot Sophia Antipolis, France
Interests: MIMO communications; WLAN; wireless femto caching network
Prof. Dr. Wan Choi

E-Mail Website
Guest Editor
School of Electrical Engineering and Computer Science (EECS), Seoul National University, Seoul 08826, Korea
Interests: Wireless distributed learning; wireless edge processing; 5G/6G communication systems

Special Issue Information

Dear Colleagues,

With the rapid proliferation of wireless devices and the emergence of new internet-based services, 5G and beyond 5G (B5G) wireless networks are required to support various use cases, such as enhanced mobile broadband (eMBB), ultra-reliable and low latency (URLLC), and massive machine type communications (mMTC). These new use cases have some different characteristics from the conventional ones, and they bring new challenges regarding traffic, interference, and control signaling. Hence, communication strategies should be redesigned to cope with the new requirements for next-generation communication systems.

In particular, multi-antenna techniques have been widely utilized in conventional communication environments as an effective tool to improve the data rate and communication reliability. However, basic assumptions in the conventional multi-antenna techniques, such as channel state information, i.i.d. channel gains, coordinated user access, and long blocklength, may no longer be valid for the new environments considered in 5G and B5G. For this reason, there is a critical need to re-examine existing multi-antenna techniques and develop them to fulfill the requirements for 5G and B5G wireless networks.

The objective of this Special Issue is to address, discuss, and present novel multi-antenna techniques for 5G and B5G wireless networks. The topics of Special Issue include, but are not limited to the following:

  • Massive MIMO for mmWave communications
  • Multi-antenna communications with short blocklength coding
  • Grant-free random access with multi-antenna devices
  • Spatial domain non-orthogonal multiple access
  • Multi-antenna technique for device-to-device communications

Dr. Jun-Pyo Hong
Dr. Jaeyoung Song
Prof. Dr. Wan Choi
Guest Editors

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Keywords

  • MIMO
  • 5G
  • B5G
  • massive MIMO
  • low latency
  • high reliability
  • massive connectivity
  • NOMA
  • grant-free access

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Published Papers (7 papers)

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12 pages, 374 KiB  
Communication
Random Beam-Based Non-Orthogonal Multiple Access for Low Latency K-User MISO Broadcast Channels
by Jung Hoon Lee, Yunjoo Kim and Jong Yeol Ryu
Sensors 2021, 21(13), 4373; https://doi.org/10.3390/s21134373 - 26 Jun 2021
Cited by 1 | Viewed by 1669
Abstract
In this paper, we propose random beam-based non-orthogonal multiple access (NOMA) for low latency multiple-input single-output (MISO) broadcast channels, where there is a target signal-to-interference-plus-noise power ratio (SINR) for each user. In our system model, there is a multi-antenna transmitter with its own [...] Read more.
In this paper, we propose random beam-based non-orthogonal multiple access (NOMA) for low latency multiple-input single-output (MISO) broadcast channels, where there is a target signal-to-interference-plus-noise power ratio (SINR) for each user. In our system model, there is a multi-antenna transmitter with its own single antenna users, and the transmitter selects and serves some of them. For low latency, the transmitter exploits random beams, which can reduce the feedback overhead for the channel acquisition, and each beam can support more than a single user with NOMA. In our proposed random beam-based NOMA, each user feeds a selected beam index, the corresponding SINR, and the channel gain, so it feeds one more scalar value compared to the conventional random beamforming. By allocating the same powers across the beams, the transmitter independently selects NOMA users for each beam, so it can also reduce the computational complexity. We optimize our proposed scheme finding the optimal user grouping and the optimal power allocation. The numerical results show that our proposed scheme outperforms the conventional random beamforming by supporting more users for each beam. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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10 pages, 1125 KiB  
Communication
Distributed Joint Optimization of Beamforming and Power Allocation for Maximizing the Energy Efficiency of Cognitive Heterogeneous Networks
by Kisong Lee
Sensors 2021, 21(9), 3186; https://doi.org/10.3390/s21093186 - 4 May 2021
Cited by 2 | Viewed by 1940
Abstract
This paper investigated an energy-efficient beamforming and power allocation strategy for cognitive heterogeneous networks with multiple-input-single-output interference channels. To maximize the sum energy efficiency of secondary users (SUs) while keeping the interference to primary networks under a predetermined threshold, I propose a distributed [...] Read more.
This paper investigated an energy-efficient beamforming and power allocation strategy for cognitive heterogeneous networks with multiple-input-single-output interference channels. To maximize the sum energy efficiency of secondary users (SUs) while keeping the interference to primary networks under a predetermined threshold, I propose a distributed resource allocation algorithm using dual methods, in which each SU updates its beamforming vector and transmit power iteratively without any information sharing until convergence. The simulation results verify that the performance of the proposed scheme is comparable to that of the optimal scheme but with a much shorter computation time. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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21 pages, 3758 KiB  
Article
Efficient Transmit Antenna Subset Selection for Multiuser Space–Time Line Code Systems
by Sangchoon Kim
Sensors 2021, 21(8), 2690; https://doi.org/10.3390/s21082690 - 11 Apr 2021
Cited by 7 | Viewed by 2024
Abstract
We consider the problem of the efficient transmit antenna subset (TAS) selection for maximizing the signal-to-interference-plus-noise ratio (SINR) of multiuser space–time line code (MU–STLC) systems. The exhaustive search for optimal TAS selection is impractical since the total number of transmit antennas increases. We [...] Read more.
We consider the problem of the efficient transmit antenna subset (TAS) selection for maximizing the signal-to-interference-plus-noise ratio (SINR) of multiuser space–time line code (MU–STLC) systems. The exhaustive search for optimal TAS selection is impractical since the total number of transmit antennas increases. We propose two efficient TAS selection schemes based on the Woodbury formula. The first is to incrementally select NS active transmit antennas among the available NT transmit antennas. To reduce the complexity of the incremental selection scheme, the Woodbury formula is employed in the optimization process. The second is to perform the decremental strategy in which the Woodbury formula is also applied to develop the low-complexity TAS selection procedure for the MU–STLC systems. Simulation results show that the proposed incremental and decremental TAS selection algorithms offer better alternatives than the existing greedy TAS selection algorithm for the MU–STLC systems. Furthermore, in terms of bit error rate, the proposed minimum mean square error decremental TAS selection algorithm turns out to outperform the existing greedy algorithm with significantly lower computational complexity. Finally, we analyze the detection SINR penalty experienced from TAS selection and the analytical quantity is shown to be well matched with simulation results. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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9 pages, 839 KiB  
Communication
Distributed Beamforming and Power Allocation for Heterogeneous Networks with MISO Interference Channel
by Kisong Lee
Sensors 2021, 21(8), 2606; https://doi.org/10.3390/s21082606 - 8 Apr 2021
Cited by 1 | Viewed by 1738
Abstract
To address the limitations of centralized resource allocation, i.e., high computational complexity and signaling overhead, a distributed beamforming and power allocation strategy is proposed for heterogeneous networks with multiple-input-single-output (MISO) interference channels. In the proposed scheme, each secondary user transceiver pair (SU TP) [...] Read more.
To address the limitations of centralized resource allocation, i.e., high computational complexity and signaling overhead, a distributed beamforming and power allocation strategy is proposed for heterogeneous networks with multiple-input-single-output (MISO) interference channels. In the proposed scheme, each secondary user transceiver pair (SU TP) determines the beamforming vector and transmits power to maximize its own spectral efficiency (SE) while keeping the interference to the primary user below a predetermined threshold, and such resource management for each SU TP is updated iteratively without any information sharing until the strategies for all SU TPs converge. The simulation confirms that the proposed scheme can achieve a performance comparable to that of a centralized approach with a much lower computation time, e.g., less than 5% degradation in SE while improving computation time by more than 10 times. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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14 pages, 614 KiB  
Article
Deep Learning Based Antenna Selection for MIMO SDR System
by Shida Zhong, Haogang Feng, Peichang Zhang, Jiajun Xu, Huancong Luo, Jihong Zhang, Tao Yuan and Lei Huang
Sensors 2020, 20(23), 6987; https://doi.org/10.3390/s20236987 - 7 Dec 2020
Cited by 13 | Viewed by 4607
Abstract
In this paper, we propose and implement a novel framework of deep learning based antenna selection (DLBAS)-aided multiple-input–multiple-output (MIMO) software defined radio (SDR) system. The system is constructed with the following three steps: (1) a MIMO SDR communication platform is first constructed, which [...] Read more.
In this paper, we propose and implement a novel framework of deep learning based antenna selection (DLBAS)-aided multiple-input–multiple-output (MIMO) software defined radio (SDR) system. The system is constructed with the following three steps: (1) a MIMO SDR communication platform is first constructed, which is capable of achieving uplink communication from users to the base station via time division duplex (TDD); (2) we use the deep neural network (DNN) from our previous work to construct a deep learning decision server to assist the MIMO SDR platform for making intelligent decision for antenna selection, which transforms the optimization-driven decision making method into a data-driven decision making method; and (3) we set up the deep learning decision server as a multithreading server to improve the resource utilization ratio. To evaluate the performance of the DLBAS-aided MIMO SDR system, a norm-based antenna selection (NBAS) scheme is selected for comparison. The results show that the proposed DLBAS scheme performed equally to the NBAS scheme in real-time and out-performed the MIMO system without AS with up to 53% improvement on average channel capacity gain. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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15 pages, 1052 KiB  
Article
User Oriented Transmit Antenna Selection in Massive Multi-User MIMO SDR Systems
by Shida Zhong, Haogang Feng, Peichang Zhang, Jiajun Xu, Lei Huang, Tao Yuan and Yongkai Huo
Sensors 2020, 20(17), 4867; https://doi.org/10.3390/s20174867 - 28 Aug 2020
Cited by 9 | Viewed by 2752
Abstract
A transmit antenna selection (TxAS) aided multi-user multiple-input multiple-output (MU-MIMO) system is proposed for operating in the MIMO downlink channel environments, which shows significant improvement in terms of higher data rate when compared to the conventional MU-MIMO systems operating without adopting TxAS, while [...] Read more.
A transmit antenna selection (TxAS) aided multi-user multiple-input multiple-output (MU-MIMO) system is proposed for operating in the MIMO downlink channel environments, which shows significant improvement in terms of higher data rate when compared to the conventional MU-MIMO systems operating without adopting TxAS, while maintaining low hardware costs. We opt for employing a simple yet efficient zero-forcing beamforming (ZFBF) linear precoding scheme at the transmitter in order to reduce the decoding complexity when considering users’ side. Moreover, considering that users within the same cell may require various qualities of service (QoS), we further propose a novel user-oriented smart TxAS (UOSTxAS) scheme, of which the main idea is to carry out AS based on the QoS requirements of different users. At last, we implement the proposed UOSTxAS scheme in the software defined radio (SDR) MIMO communication hardware platform, which is the first prototype hardware system that runs the UOSTxAS MU-MIMO scheme. Our results show that, by employing TxAS, the proposed UOSTxAS scheme is capable of offering higher data rates for priority users, while reasonably ensuring the performance of the common users requiring lower rates both in simulation and in the implemented SDR MIMO communication platform. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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14 pages, 3531 KiB  
Letter
Position Tracking Techniques Using Multiple Receivers for Anti-Drone Systems
by Jae-Min Shin, Yu-Sin Kim, Tae-Won Ban, Suna Choi, Kyu-Min Kang and Jong-Yeol Ryu
Sensors 2021, 21(1), 35; https://doi.org/10.3390/s21010035 - 23 Dec 2020
Cited by 13 | Viewed by 3671
Abstract
The need for drone traffic control management has emerged as the demand for drones increased. Particularly, in order to control unauthorized drones, the systems to detect and track drones have to be developed. In this paper, we propose the drone position tracking system [...] Read more.
The need for drone traffic control management has emerged as the demand for drones increased. Particularly, in order to control unauthorized drones, the systems to detect and track drones have to be developed. In this paper, we propose the drone position tracking system using multiple Bluetooth low energy (BLE) receivers. The proposed system first estimates the target’s location, which consists of the distance and angle, while using the received signal strength indication (RSSI) signals at four BLE receivers and gradually tracks the target based on the estimated distance and angle. We propose two tracking algorithms, depending on the estimation method and also apply the memory process, improving the tracking performance by using stored previous movement information. We evaluate the proposed system’s performance in terms of the average number of movements that are required to track and the tracking success rate. Full article
(This article belongs to the Special Issue Multi-Antenna Techniques for 5G and beyond 5G Communications)
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