Studies in Computational Intelligence
Health monitoring is considered as a gigantic problem in emerging nations, particularly in inaccessible region. The development in radio telecommunication has upgraded the smart hospital in voluminous aspects. One of the visions of 5G communication systems is to deliver a dependable, protected and fast radio at anyplace and anytime for the forthcoming smart health care. To realize this, the 5G system must attained low peak to average power ratio (PAPR), efficient spectrum, small latency and faster data-rate. In the present correspondence, our work mainly focused to introduce a novel PAPR reduction technique, which is one of the necessities of 5G based smart hospital. Artificial intelligence (AI) based genetic algorithm (GA) supported selective mapping Sequence (SLM), known as GA-SLM is suggested to diminish the PAPR of the NOMA system. However, the required multiplications and additions for SLM techniques are too much, which increase the complexity of the system. Hence, it important to proposed AI techniques to minimize the intricacy. The investigation outcomes indicate that the efficiency of the GA-SLM outperforms the typical PAPR procedures.