**Abstract**

Energy efficiency is the use of technology that requires less energy to perform the same task. It was considered to introduce optimized energy efficiency by using machine learning to reduce power consumption at communication base station (BTS) sites. This process involves reviewing relevant work to identify defects, characterizing and determining the power consumption of the cell site under investigation, developing a SIMULINK model for the cell site under investigation, and identifying the module. It also includes optimizing high power consumption; design a machine learning rule base to monitor the power consumption of the module. Train artificial neural network (ANN) on machine learning rules designed to reduce cell power consumption, thereby improving network performance. The next step is developing an algorithm to implement it, and finally, to design a power consumption model for the network under investigation. The results obtained after a large simulation show that the traditional maximum power consumed at the cell site is 5746 kW, while the power when machine learning is injected into the system is 4733 kW. Integrating machine learning into the system resulted in 4731 kW, an 8.9% performance improvement.

**Keywords:** optimized, energy efficiency, reduction of power consumption, telecommunication base transceiver station, machine learning

#### **1. Introduction**

The trouble of power efficiency is one of the main challenges dealing with wireless cell community vendors around the world today. In Nigeria, some cell network vendors have been affected, resulting in the closing down of websites due to the trouble of energy efficiency. To handle this situation, which offers power consumption reduction in a base station (BS), several processes have been adopted that led to the introduction of green conversation techniques. Power amplifier (PA) improvement has attracted a good deal of attention because it devours the greatest proportion of the strength consumption of BSs. In cellular communications, the energy amplifier in a macro phone BS consumes the most energy, as a great deal as 65% of the complete power bumps off via all BS elements. The trouble is that the strength efficiency of PA is doable solely with interior equipment, but now not with external prerequisites such as not knowing the wide variety of users asking for getting entry to the BS at a time. This changes the electricity effectivity done through the internal equipment. It is normal that excessive bit error fees result in

poor conversation overall performance [1]. On the different hand, Akbari et al. [2] certainly emphasizes the need to integrate ultracapacitors into the device for energy efficiency. The author of egalitarianism [3] emphasized the need to redefine wi-fi conversation to enhance its effectiveness. Bazzi et al. [4] reiterated that greater throughput is a core function of multiradio efficiency. Optimization issues seem to be for most or minimum values that a character can take. In the absolute extremes section, we noticed how to resolve sure optimization problems. Here we have located the maximum and minimum values that the function takes in the interval. Machine learning is a synthetic intelligence (AI) software that provides systems with the ability to automatically learn and improve. Machine getting to know teaches computer systems what people take for granted, that is, what they learn from experience. Machine getting to know algorithms use computational methods to "learn" statistics without delay from data, except relying on specific equations as a model. The algorithm adaptively improves overall performance as the wide variety of samples on hand for education increases. The development and modifications that have taken vicinity in the enterprise lately have entered a new phase in parallel with the improvement of computer technology, fuzzy logic, and, ultimately, a completely new subject of synthetic intelligence, the study [5] reveals that artificial talent (AI) is growing because of its manageable to be predictive and sourcing. Renewable strength sources such as wind and solar are very useful and clean sources; their indepleteable houses help in enhancing or smoothing performance in aggregate with different sources, such as biomass, in particular in rural areas. The methodology to achieve the intention of this work is the adherence to the mentioned research goals, which has to do with the tabulation of the gathered data and characterization of the current telecommunication primary based transceiver underneath learn about [6].
