Joint Design for MIMO Radar and Downlink Communication Systems Coexistence

Author(s):  
Ziyang Cheng ◽  
Bin Liao ◽  
Zishu He ◽  
Jun Li ◽  
Julan Xie
2020 ◽  
Vol 68 ◽  
pp. 5602-5616
Author(s):  
Jie Li ◽  
Guisheng Liao ◽  
Yan Huang ◽  
Zhen Zhang ◽  
Arye Nehorai

2019 ◽  
Vol 26 (11) ◽  
pp. 1648-1652 ◽  
Author(s):  
Junwei Zhou ◽  
Hongbin Li ◽  
Wei Cui
Keyword(s):  

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.


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