scholarly journals Performance Analysis of Data Transmission for Joint Radar and Communication Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jianhua Lu ◽  
Tuanwei Tian ◽  
Yanli Tang ◽  
Bin Tang
Keyword(s):  
Data Transmission ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Average Power ◽  
Spectrum Efficiency ◽  
Radar Signal ◽  
Interference Avoidance ◽  
Data Throughput ◽  
Radar Echo ◽  
Significant Performance

This paper investigates the problem of data transmission for the joint radar and communication systems (JRCSs). The performance of the JRCS is characterized by data throughput related to the radar echo data (RED) and communication data rate (CDR). Two spectral coexistence schemes are proposed based on the degree of spectrum sharing for radar and communication, i.e., the isolated subfrequency band (ISFB) and mix-used frequency band (MUFB) schemes. Firstly, the signals of radar and communication are operated on the isolated subcarriers, enabling the received signals to be processed independently and bringing the advantage of interference avoidance. Secondly, the signals of radar and communication can be jointly operated on the same subcarriers for the MUFB scheme, which enhances the spectrum efficiency. Unlike the ISFB scheme, the CDR of the MUFB scheme is maximized along with the interference from the radar signal, and meanwhile, the allocated radar power on each subcarrier is derived by maximizing the radar mutual information. Numerical results show that the MUFB scheme significantly improves the performance of data transmission over the ISFB scheme, and a significant performance gain in the data transmission can be achieved, compared to the average power allocation case.

A Method for Designing Low Peak to Average Power Cognitive Radar Waveform

2014 ◽  
Vol 716-717 ◽  
pp. 1055-1059
Author(s):  
Xue Mei Wang ◽  
Chun Yang Wang ◽  
Yu Chen ◽  
Yan Xin Yu ◽  
Hong Yan Sun
Keyword(s):  
Communication Systems ◽  
Average Power ◽  
Radar Signal ◽  
Transform Domain ◽  
Cognitive Radar ◽  
Complementary Sequence ◽  
Detection Range ◽  
Transmitter Power ◽  
Distant Target ◽  
Radar Echo

In this paper, the basis function of TDCS system (Transform Domain Communication System) is used to design cognitive radar transmitter waveform. Based on the noise environment, the waveform can be adjusted adaptively. Then after clipping to reduce the PAPR (Peak to Average Power Ratio) of radar echo signal, the obtained signal is used as the next launch of the radar signal. The cognitive radar transmitter requires a nonlinear waveform to improve the efficiency of radar transmitter power amplifier, so reducing the PAPR of signal is essential. This paper presents the gray complementary sequence is applied to TDCS communication systems, and then it needs to reduce PAPR of signals by clipping. Proven, PAPR of the transmitted signal is maintained at about 3.25dB, and the signal has a low probability of intercept, high anti-interference ability and distant target detection range.

scholarly journals Autoencoder-bank Based Design for Adaptive Channel-Blind Robust Transmission

2020 ◽  
Author(s):  
Hossein Safi ◽  
Mohammad Akbari ◽  
Elaheh Vaezpour ◽  
Saeedeh Parsaeefard ◽  
Raed M. Shubair
Keyword(s):  
Data Transmission ◽  
Communication Systems ◽  
Channel Model ◽  
Average Power ◽  
Adaptive Scheme ◽  
Pilot Symbols ◽  
Average Power Consumption ◽  
Channel Conditions ◽  
Robust Transmission ◽  
Average Block

Abstract The idea of employing deep autoencoders (AEs) has been recently proposed to capture the end-to-end performance in the physical layer of communication systems. However, most of the current methods for applying AEs are developed based on the assumption that there is an explicit channel model for training that matches the actual channel model in the online transmission. Since the actual channel varies over time, this imposes a major limitation on employing AE-based systems. In this paper, without relying on an explicit channel model, we propose an adaptive scheme to increase the reliability of an AE-based communication system over different channel conditions. More precisely, we divide the interval of random channel coefficients into n sub-intervals. Subsequently, in the offline training phase, we employ an AE bank consisting of n pairs of encoder and decoder and perform training over the sub-intervals. Then, in the online transmission phase, based on the actual channel conditions, the optimal pair of encoder and decoder is selected for data transmission in terms of satisfying an average block error rate (BLER) constraint imposed on the system. To monitor actual channel conditions for adopting the adaptive scheme, we assume a realistic scenario where the instantaneous channel gain is not known to Tx/Rx and it is blindly estimated at the RX, i.e., without using any pilot symbols. Our simulation results confirms the superiority of the proposed adaptive scheme over a non-adaptive scenario in terms of average power consumption. For instance, when the target average BLER is equal to 10−4 , our proposed algorithm with n = 5 can achieve a performance gain over 1.2 dB compared with a non-adaptive scheme

scholarly journals Autoencoder-Bank Based Design for Adaptive Channel-Blind Robust Transmission

2020 ◽  
Author(s):  
Hossein Safi ◽  
Mohammad Akbari ◽  
Elahe Vaezpour ◽  
Saeedeh Parsaeefard ◽  
Raed M. Shubair
Keyword(s):  
Data Transmission ◽  
Communication Systems ◽  
Channel Model ◽  
Average Power ◽  
Adaptive Scheme ◽  
Pilot Symbols ◽  
Average Power Consumption ◽  
Channel Conditions ◽  
Robust Transmission ◽  
Average Block

Abstract The idea of employing deep autoencoders (AEs) has been recently proposed to capture the end-to-end performance in the physical layer of communication systems. However, most of the current methods for applying AEs are developed based on the assumption that there is an explicit channel model for training that matches the actual channel model in the online transmission. Since the actual channel varies over time, this imposes a major limitation on employing AE-based systems. In this paper, without relying on an explicit channel model, we propose an adaptive scheme to increase the reliability of an AE-based communication system over different channel conditions. More precisely, we divide the interval of random channel coefficients into n sub-intervals. Subsequently, in the offline training phase, we employ an AE bank consisting of n pairs of encoder and decoder and perform training over the sub-intervals. Then, in the online transmission phase, based on the actual channel conditions, the optimal pair of encoder and decoder is selected for data transmission in terms of satisfying an average block error rate (BLER) constraint imposed on the system. To monitor actual channel conditions for adopting the adaptive scheme, we assume a realistic scenario where the instantaneous channel gain is not known to Tx/Rx and it is blindly estimated at the RX, i.e., without using any pilot symbols. Our simulation results confirms the superiority of the proposed adaptive scheme over a non-adaptive scenario in terms of average power consumption. For instance, when the target average BLER is equal to 10−4, our proposed algorithm with n = 5 can achieve a performance gain over 1.2 dB compared with a non-adaptive scheme.

scholarly journals Opportunistic Interference Alignment for Spectrum Sharing between Radar and Communication Systems

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4868
Author(s):  
Dong-Hwan Kim ◽  
Janghyuk Youn ◽  
Bang Chul Jung
Keyword(s):  
Communication System ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Interference Alignment ◽  
Radar System ◽  
Cellular Communication ◽  
Radar Signal ◽  
Rate Performance ◽  
Communication Signals ◽  
Sum Rate

In this paper, we propose a novel opportunistic interference alignment technique for spectrum-shared radar and uplink cellular communication systems where both systems are equipped with multiple antennas. In the proposed OIA technique, the radar system sends its signal so that the radar signal is received into interference space at base stations (BSs) of the cellular system, while each uplink user (UE) generates its transmit beamforming vector so that communication signals are received within interference space at the radar receiver. Moreover, to achieve better sum-rate performance of the cellular communication system, the BS selects the UEs which results in sufficiently small interference to other cells for the uplink communication. With the proposed OIA technique, detection performance of the radar system is protected, while the communication system achieves satisfactory sum-rate performance. Through extensive computer simulations, we show that the performances of both radar and communication systems with the proposed technique significantly outperform a conventional null-space projection based spectrum sharing scheme.

scholarly journals Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3584
Author(s):  
Milembolo Miantezila Junior ◽  
Bin Guo ◽  
Chenjie Zhang ◽  
Xuemei Bai
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Null Space ◽  
Base Station ◽  
Base Stations ◽  
Small Cells ◽  
Data Traffic ◽  
New Approach ◽  
Lte Advanced

Cellular network operators are predicting an increase in space of more than 200 percent to carry the move and tremendous increase of total users in data traffic. The growing of investments in infrastructure such as a large number of small cells, particularly the technologies such as LTE-Advanced and 6G Technology, can assist in mitigating this challenge moderately. In this paper, we suggest a projection study in spectrum sharing of radar multi-input and multi-output, and mobile LTE multi-input multi-output communication systems near m base stations (BS). The radar multi-input multi-output and mobile LTE communication systems split different interference channels. The new approach based on radar projection signal detection has been proposed for free interference disturbance channel with radar multi-input multi-output and mobile LTE multi-input multi-output by using a new proposed interference cancellation algorithm. We chose the channel of interference with the best free channel, and the detected signal of radar was projected to null space. The goal is to remove all interferences from the radar multi-input multi-output and to cancel any disturbance sources from a chosen mobile Communication Base Station. The experimental results showed that the new approach performs very well and can optimize Spectrum Access.

scholarly journals Data Downlink System in the Vast IOT Node Condition Assisted by UAV, Large Intelligent Surface, and Power and Data Beacon

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5748
Author(s):  
Zhibo Zhang ◽  
Qing Chang ◽  
Na Zhao ◽  
Chen Li ◽  
Tianrun Li
Keyword(s):  
Communication Systems ◽  
Optimization Problems ◽  
Minimum Energy ◽  
Numerical Algorithms ◽  
Flight Trajectory ◽  
Performance Improvements ◽  
Minimum Energy Consumption ◽  
Significant Performance ◽  
Downlink System ◽  
The Internet Of Things

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.

scholarly journals Transmission Strategy Design and Resource Allocation in D2D Multicast Cooperative Communications with SWIPT

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Chenfan Weng ◽  
Dingcheng Yang ◽  
Jun Wan ◽  
Lin Xiao ◽  
Chuanqi Zhu
Keyword(s):  
Resource Allocation ◽  
Cooperative Communications ◽  
Communication Systems ◽  
Spectrum Efficiency ◽  
Second Step ◽  
Total System ◽  
Power Splitting ◽  
Transmission Strategy ◽  
Multiple Receivers ◽  
Strategy Design

This paper proposes a new transmission strategy for device-to-device (D2D) multicast cooperative communication systems based on Simultaneous Wireless Information and Power Transfer (SWIPT) technology. The transmission block is divided into two slots. In the first slot, the source user transmits the information and energy to the help user by SWIPT. In the second slot, the help user uses the cellular spectrum and forwards the information to multiple receivers by using harvested energy. In this paper, we aim to maximize the total system rate, and to tackle the problem, we propose a two-step scheme: In the first step, the resource allocation problem is solved by linear programming. In the second step, the power-splitting coefficient value is obtained by taking the benefit of help user into account. Numerical results show that the proposed strategy not only effectively improves the overall throughput and spectrum efficiency but also motivates the cooperation.

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