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Introduction
The usage of wireless sensor networks is becoming essential and has been much improved over recent decades. There are a lot of Micro Electro Mechanical Systems (MEMs) in wireless sensor networks (WSNs) which have limited capability (during their power allocation and processing). These MEMs have to measure and report physical variables related to their environment. The tiny sensors which deployed in the target area, or very close to the subject observed phenomenon, are low power, low cost, and lightweight systems in order to sense the features like temperature, pressure, movement or intrusion in the monitored area. The recorded data which is collected by sensors will be transmitted to the target node (processing node) called “sink” with higher energy and processing capability. In the processing node (PN), data would be filtered, compiled and sent. Since all the elements in this process need energy, sensors can only transmit a limited amount of data. Virtually, the sensors situation is hard to access, so if it is not impossible, it would be very hard to change batteries or recharge them; that’s why the energy efficiency is a critical issue for the design of these networks. It has been proven that the multi-hop data routing toward the PN is more energy efficient than direct transmission. The other challenging point in this issue is consideration of the limited size of the nodes. In the practice, we can only plant restricted numbers of antennas in each node. However, if the multiple nodes could cooperate with each other, they would be able to arrange an artificial array antenna to achieve the desirable spatial variety. We called such schemes 'cooperative pattern'.

There are 5 strategies to save energy: Setting up an appropriate timetable of the sensor state according to its sleep and active modes. •	Properly clustering intervals and data aggregation methods. •	Coding strategies in order to reduce the amount of data. •	Making efforts to ensure an optimal trade-off between energy consumption and connectivity •	The conventional methods related to channel access and transmission protocols.

Previous works
Recently many efforts and researches have been done regarding different aspects of cooperative telecommunication systems and its models. Guan Xin et al. and Wei et al. have used Hierarchical clustering algorithms to save energy in WSN. Heinzelman et al. proposed Low-Energy Adaptive Clustering Hierarchy (LEACH), one of the most popular hierarchical routing algorithms for WSN, to form clusters of sensor nodes based on the received signal strength and use local cluster heads as routers to the sink. Stefano et al. and Landman et al. suppose that no beam formation exists in transmitters and cooperative protocols, and their initial setup consists of a transmitter, receiver and a single node relay. Hasna et al. achieved to an energy allocation model among the relay nodes in order to minimize connection corruptions. In the energy efficiency has been challenged and they tried to criticize energy issue in a clustered WSN in which sensors cooperate with each other to send signals. It has been shown that if the distance between clusters is large enough (compared to the distance of nodes in those clusters) then cooperative schemes can enormously reduce the consumption of energy. Abidoye et al. proposed the even size clustering model. They considered this fact that cluster heads close to the Base station (BS) are burdened with heavy relay traffic, so they consume more energy as compared to CHs which are far from the BS. This fact results in a short lifetime of these CHs, which is called Hotspot problem. They have solved this problem by unequal clustering. Rupert et al. continued the above idea and proposed a new method based on the lifetime of sensor nodes and their consumption of energy. They used delta modulation to reduce the size of the data packet.