Method and system for optimizing transceiver spectrum sharing
A method and system for providing a cooperative spectrum sharing model that jointly optimizes primary user equipment parameters for improved frequency agility and performance while mitigating mutual interference between the primary user equipment and secondary user equipment. Spectrum sensing is implemented to form a power spectral estimate of the electromagnetic environment (EME) and apply multi-objective optimization to adjust the operational parameters of the primary user equipment to mitigate interference.
1. A system for optimizing radio frequency (RF) spectrum sharing comprising:
a radar system;
a RF communication system configured to transmit and receive signals to user equipment;
a spectrum sensing system, coupled to the radar system and the RF communication system, and comprising at least one computer processor configured to sense the RF spectral environment proximate the radar system and the RF communication system, process the sensed RF spectral environment using multi-objective optimization to jointly determine an optimal operational RF spectrum for each of the radar system and the RF communication system and control operational parameters of the radar system and the RF communication system to optimize RF spectrum sharing amongst the radar system and the RF communication system,
wherein the multi-objective optimization comprises a joint determination of operational frequencies, bandwidths, and power outputs of each of the radar system and the RF communication system together, at the same time, which optimize RF spectrum sharing between them; and
wherein the multi-objective optimization also takes into account co-channel interference between the radar system users, the RF communication system users, and any other RF systems.
2. The system of claim 1 wherein the processing utilizes multi-objective processing to maximize a first objective function of radar signal to interference plus noise ratio (SINR), a second objective function of radar range resolution, and a third objective function of radio capacity of the user equipment, together, at the same time.
3. The system of claim 2 wherein multi-objective processing is performed using a genetic algorithm.
4. The system of claim 3 wherein the genetic algorithm is performed using a Multi-objective Genetic Algorithm (MOGA), Niched Pareto Genetic Algorithm (NPGA), Weight-based Genetic Algorithm (WBGA), Random Weighted Genetic Algorithm (RWGA), Nondominated Sorting Genetic Algorithm (NSGA), Strength Pareto Evolutionary Algorithm (SPEA), improved SPEA (SPEA2), Pareto-Archived Evolution Strategy (PAES), Pareto Envelope-based Selection Algorithm (PESA), Region-based Selection in Evolutionary Multiobjective Optimization (PESA-II), Fast Nondominated Sorting Genetic Algorithm (NSGA-II), Multi-objective Evolutionary Algorithm (MEA), Micro-GA, Rank-Density Based Genetic Algorithm (RDGA), or Dynamic Multi-objective Evolutionary Algorithm (DMOEA) approach.
5. The system of claim 2 , wherein the first objective function of the radar SINR is defined according to Equation 1; the second objective function of the radar range resolution is defined according to Equation 4; and third objective function of the user equipment capacity is defined according to Equation 5.
6. The system of claim 1 , wherein the radar system and the RF communication system each comprise primary user equipment.
7. The system of claim 6 , wherein the multi-objective optimization of the primary user equipment also takes into account any background RF interference from any secondary user equipment.
8. The system of claim 7 , wherein the radar system and the RF communication system have with equal rights to the same shared spectrum.
9. A method of optimizing radio frequency (RF) spectrum sharing between a radar system and a RF communication system configured to transmit and receive RF signals to user equipment, the method comprising:
sensing a RF spectral environment proximate the radar system and the RF communication system;
processing the sensed RF spectral environment using multi-objective optimization to jointly determine an optimal operational RF spectrum for each of the radar system and the RF communication system; and
controlling operational parameters of the radar system and the RF communication system to optimize RF spectrum sharing amongst the radar system and the RF communication system,
wherein the multi-objective optimization comprises a joint determination of operational frequencies, bandwidths, and power outputs of each of the radar system and the RF communication system together, at the same time, which optimize RF spectrum sharing between them; and
wherein the multi-objective optimization also takes into account co-channel interference between the radar system users, the RF communication system users, and any other RF systems.
10. The method of claim 9 wherein the processing further comprises multi-objective processing to maximize a first objective function of radar signal to interference plus noise ratio (SINR), a second objective function of radar range resolution, and a third objective function of radio capacity of the user equipment, together, at the same time.
11. The system of claim 10 wherein multi-objective processing comprises executing a genetic algorithm.
12. The system of claim 11 wherein the genetic algorithm is a Multi-objective Genetic Algorithm (MOGA), Niched Pareto Genetic Algorithm (NPGA), Weight-based Genetic Algorithm (WBGA), Random Weighted Genetic Algorithm (RWGA), Nondominated Sorting Genetic Algorithm (NSGA), Strength Pareto Evolutionary Algorithm (SPEA), improved SPEA (SPEA2), Pareto-Archived Evolution Strategy (PAES), Pareto Envelope-based Selection Algorithm (PESA), Region-based Selection in Evolutionary Multiobjective Optimization (PESA-II), Fast Nondominated Sorting Genetic Algorithm (NSGA-II), Multi-objective Evolutionary Algorithm (MEA), Micro-GA, Rank-Density Based Genetic Algorithm (RDGA), or Dynamic Multi-objective Evolutionary Algorithm (DMOEA) approach.
13. The method of claim 10 , wherein the first objective function of the radar SINR is defined according to Equation 1; the second objective function of the radar range resolution is defined according to Equation 4; and third objective function of the user equipment capacity is defined according to Equation 5.
14. The method of claim 9 , wherein the radar system and the RF communication system each comprise primary user equipment.
15. The method of claim 14 , wherein the multi-objective optimization of the primary user equipment also takes into account any background RF interference from any secondary RF user equipment.
16. A non-transitory computer readable medium having software instructions that, when executed by at least one computer processor, perform a method of optimizing radio frequency (RF) spectrum sharing between a radar system and a RF communication system which is configured to transmit and receive RF signals to user equipment, the method comprising:
sensing a RF spectral environment proximate the radar system and the RF communication system;
processing the sensed RF spectral environment using multi-objective optimization to jointly determine an optimal operational RF spectrum for each of the radar system and the RF communication system; and
controlling operational parameters of the radar system and the RF communication system to optimize RF spectrum sharing amongst the radar system and the RF communication system,
wherein the multi-objective optimization comprises a joint determination of operational frequencies, bandwidths, and power outputs of each of the radar system and the RF communication system together, at the same time, which optimize RF spectrum sharing between them; and
wherein the multi-objective optimization also takes into account co-channel interference between the radar system users, the RF communication system users, and any other RF systems.
17. The method of claim 16 wherein the processing further comprises multi-objective processing to maximize a first objective function of radar signal to interference plus noise ratio (SINR), a second objective function of radar range resolution, and a third objective function of radio capacity of the user equipment, together, at the same time.
18. The method of claim 17 wherein multi-objective processing comprises executing a genetic algorithm.
19. The method of claim 18 wherein the genetic algorithm is Multi-objective Genetic Algorithm (MOGA), Niched Pareto Genetic Algorithm (NPGA), Weight-based Genetic Algorithm (WBGA), Random Weighted Genetic Algorithm (RWGA), Nondominated Sorting Genetic Algorithm (NSGA), Strength Pareto Evolutionary Algorithm (SPEA), improved SPEA (SPEA2), Pareto-Archived Evolution Strategy (PAES), Pareto Envelope-based Selection Algorithm (PESA), Region-based Selection in Evolutionary Multiobjective Optimization (PESA-II), Fast Nondominated Sorting Genetic Algorithm (NSGA-II), Multi-objective Evolutionary Algorithm (MEA), Micro-GA, Rank-Density Based Genetic Algorithm (RDGA), or Dynamic Multi-objective Evolutionary Algorithm (DMOEA) approach.
20. The method of claim 17 , wherein the first objective function of the radar SINR is defined according to Equation 1; the second objective function of the radar range resolution is defined according to Equation 4; and third objective function of the user equipment capacity is defined according to Equation 5.
21. The method of claim 16 wherein controlling the operational parameters comprises modifying the center frequencies, bandwidths and output powers of each of the radar system and the RF communication system.
22. The method of claim 16 , wherein the radar system and the RF communication system each comprise primary user equipment.
23. The method of claim 22 , wherein the multi-objective optimization of the primary user equipment also takes into account any background RF interference from any secondary RF user equipment.