scholarly journals Multiple Power Allocation Game Schemes for Spectrum Coexistence Model Between Multistatic MIMO Radar Sensors and MU Communication

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6216
Author(s):  
Bin He ◽  
Hongtao Su
Keyword(s):  
Power Allocation ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Iterative Algorithms ◽  
Mimo Radar ◽  
Base Station ◽  
Radar Sensors ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Study Power

The normal operations of radar systems and communication systems under the condition of spectrum coexistence are facing a huge challenge. This paper uses game theory to study power allocation problems between multistatic multiple-input multiple-output (MIMO) radars and downlink communication. In the case of spectrum coexistence, radars, base station (BS) and multi-user (MU) have the working state of receiving and transmitting signals, which can cause unnecessary interferences to different systems. Therefore, when they work together, they should try to suppress mutual interferences. Firstly, the signal from BS is considered as interference when radar detects and tracks targets. A supermodular power allocation game (PAG) model is established and the existence and uniqueness of the Nash equilibrium (NE) in this game are proved. In addition, the power allocation problem from BS to MU is also analyzed, and two Stackelberg PAG models are constructed. It is proved that the NE of each game exists and is unique. Simultaneously, two Stackelberg power allocation iterative algorithms converge to the NEs. Finally, numerical results verify the convergence of the proposed PAG algorithms.

scholarly journals Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1844
Author(s):  
Minhoe Kim ◽  
Woongsup Lee ◽  
Dong-Ho Cho
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Q Learning ◽  
Multiple Input ◽  
Beam Selection ◽  
Input Multiple Output ◽  
Optimal Beam ◽  
Resource Allocation Scheme

In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.

scholarly journals Adaptive Energy Efficiency Based Power Allocation for MIMO Radar Network

2019 ◽  
Vol 9 (1) ◽  
pp. 1720-1727
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Power Allocation ◽  
Target Detection ◽  
Communication Systems ◽  
Multiple Antennas ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Ratio Test ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) radar is used extensively due to its application of simultaneous transmission and reception of multiple signals through multiple antennas or channels. MIMO radar receives enormous attention in communication technologies due to its better target detection, higher resolution and improved accurate target parameter estimation. The MIMO radar has several antennas for transmitting the information and also the reflected signals from the target is received by the multiple antennas and it mainly used in military and civilian fields. But sometimes the performance of the MIMO radars is degraded due to its limited power. So the optimum power allocation is required in the communication systems of MIMO radar to improve its performance. In this paper, an Energy Efficiency based Power Allocation (EEPA) is used to allocate the power to a user of the clusters and also across the clusters. Here, the MIMO radars are clustered by using a naive bayes classifier. Subsequently, an efficient target detection is achieved by using Generalized Likelihood Ratio Test (GLRT) and then the clusters are divided into primary and distributive clusters based on the distance from the target. Here, the proposed methodology is named as EEPA-GLRT and the implementation of this MIMO radar system with an effective power allocation is done by Labview. The performance of the EEPA-GLRT methodology is analyzed in terms of the power consumption of various clusters. The performance of the EEPA-GLRT methodology is compared with Generalized Nash Game (GNG) method and it shows the power consumption of EEPA-GLRT is 0.0549 for cluster 1 of scenario 1, which is less when compared to the GNG method.

scholarly journals An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems

2020 ◽  
Vol 10 (13) ◽  
pp. 4547 ◽  
Author(s):  
Woon-Sang Lee ◽  
Jae-Hyun Ro ◽  
Young-Hwan You ◽  
Duckdong Hwang ◽  
Hyoung-Kyu Song
Keyword(s):  
Antenna Array ◽  
High Throughput ◽  
Communication Systems ◽  
High Performance ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Data Rate ◽  
Multiple Input ◽  
Input Multiple Output

Recently, as the demand for data rate of users has increased, wireless communication systems have aimed to offer high throughput. For this reason, various techniques which guarantee high performance have been invented, such as massive multiple-input multiple-output (MIMO). However, the implementation of huge base station (BS) antenna array and decrease of reliability as the number of users increases are chief obstacles. In order to mitigate these problems, this paper proposes an adaptive precoder which provides high throughput and bit error rate (BER) performances to achieve the desired data rate in multi user (MU) MIMO downlink systems which have a practical BS antenna array (up to 16). The proposed scheme is optimized with a modified minimum mean square error (MMSE) criterion in order to improve BER gain and reduce data streams in order to obtain diversity gain at low signal to noise ratio (SNR). It is shown that the BER and throughput performances of the proposed scheme are improved.

scholarly journals Study of 5G-NR-MIMO Links in the Presence of an Interferer

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 732
Author(s):  
Avner Elgam ◽  
Yael Balal ◽  
Yosef Pinhasi
Keyword(s):  
Mobile Networks ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Local Area ◽  
Maximum Energy ◽  
Base Station ◽  
Small Cells ◽  
Diversity Coding ◽  
Shift Keying ◽  
Input Multiple Output

Many communication systems are based on the Multiple Input, Multiple Output (MIMO) scheme, and Orthogonal Space–time Block Transmit diversity Coding (OSTBC), combined with Maximal Ratio Receive Combining (MRRC), to create an optimal diversity system. A system with optimal diversity fixes and optimizes the channel’s effects under multi-path and Rayleigh fading with maximum energy efficiency; however, the challenge does not end with dealing with the channel destruction of the multi-path impacts. Susceptibility to interference is a significant vulnerability in future wireless mobile networks. The 5th Generation New Radio (5G-NR) technologies bring hundreds of small cells and pieces of User Equipment (UE) per indoor or outdoor local area scenario under a specific Long Term Evolution (LTE)-based station (e-NodeB), or under 5G-NR base-station (g-NodeB). It is necessary to study issues that deal with many interference signals, and smart jammers from advanced communication equipment cause deterioration in the links between the UE, the small cells, and the NodeB. In this paper, we study and present the significant impact and performances of 2×2 Alamouti Phase-Shift Keying (PSK) modulation techniques in the presence of an interferer and a smart jammer. The destructive effects affecting the MIMO array and the advanced diversity technique without closed-loop MIMO are analyzed. The performance is evaluated in terms of Bit Error Rate (BER) vs. Signal to Interference Ratio (SIR). In addition, we proved the impairment of the orthogonal spectrum assumption mathematically.

scholarly journals Angle Estimation for MIMO Radar in the Presence of Gain-Phase Errors with One Instrumental Tx/Rx Sensor: A Theoretical and Numerical Study

2021 ◽  
Vol 13 (15) ◽  
pp. 2964
Author(s):  
Fangqing Wen ◽  
Junpeng Shi ◽  
Xinhai Wang ◽  
Lin Wang
Keyword(s):  
Numerical Study ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Phase Errors ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Angle Pair ◽  
Parallel Factor ◽  
Parafac Decomposition

Ideal transmitting and receiving (Tx/Rx) array response is always desirable in multiple-input multiple-output (MIMO) radar. In practice, nevertheless, Tx/Rx arrays may be susceptible to unknown gain-phase errors (GPE) and yield seriously decreased positioning accuracy. This paper focuses on the direction-of-departure (DOD) and direction-of-arrival (DOA) problem in bistatic MIMO radar with unknown gain-phase errors (GPE). A novel parallel factor (PARAFAC) estimator is proposed. The factor matrices containing DOD and DOA are firstly obtained via PARAFAC decomposition. One DOD-DOA pair estimation is then accomplished from the spectrum searching. Thereafter, the remainder DOD and DOA are achieved by the least squares technique with the previous estimated angle pair. The proposed estimator is analyzed in detail. It only requires one instrumental Tx/Rx sensor, and it outperforms the state-of-the-art algorithms. Numerical simulations verify the theoretical advantages.

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