## 1 Introduction  
Radio telecommunications are susceptible to fading and fluctuations in signal intensity, which can result in a significant deterioration in system efficacy. Multiple-input multiple-output (MIMO) systems are a group of strategies that have proven effective in practice for dealing with this issue [1, 2, 3]. The fundamental concept underlying these systems is to take advantage of the scattering environment formed by multiple antennas to maximize the achieved reliability and throughput. The two principal categories of MIMO structures are known as spatial diversity and spatial multiplexing. The former improves the reliability by capitalizing on the fact that copies of the broadcast signal in both time and space arrive at the receiver influenced by distinct fading coefficients. The latter raises throughput by transmitting numerous distinct data streams into MIMO channels. In today's world, MIMO systems are at the center of a number of cutting-edge communications technologies, including mobile communications, such as High-Speed Packet Access (HSPA) and Long Term Evolution (LTE) [4]. Further, they are essential to the evolution of the area of 5G and beyond [5]. Additionally, the Institute of Electrical and Electronics Engineers (IEEE) has incorporated MIMO approaches for WI-FI systems, such as IEEE802.11n and IEEE802.11 ac [6]. A further giant leap forward in the development of wireless communication networks is the appearance of cooperative technologies. Various stations in a network collaborate in cooperative communications by bouncing each other's data, establishing a virtualized antenna array, and achieving distributed spatial diversity. The enhanced functionality of cooperative communications, such as connection consistency, capacity, broadcasting range, and simplicity of deployment, has caught the attention of researchers and developers across academia and private sectors [7; 8]. Two stages are commonly included in the construction of a radio cooperative broadcast. In the first stage, data simultaneously propagate from the source node to the relay and final destination. During the subsequent stage, the source is idle while the relay forwards the data to its intended destination. The relay's processing of the signal sent by the originating node is a crucial aspect of cooperative transmissions. Multiple handling approaches give rise to relaying protocols, such as amplify-and-forward (AF) and decode-and-forward (DF) [9; 10]. The former is one of the fundamental cooperative techniques, such that a relay merely passes a scaled form of the collected signals. The latter is another frequent option, in which the relay detects the incoming signals and re-encodes them before broadcasting them to the endpoint. The destination reaches a judgment by integrating information from the source and relays. Spatial diversity is always possible due to the fact that the destination gets many copies of the signal across several independent pathways. The process of signal categorization (SC) comprises the gathering of a variety of illustrative properties that can be used to identify the sent signal from a variety of other alternatives [11; 12; 13]. This is necessary in order to guarantee accurate demodulation of the received waveforms and effective restoration of the sent data. This technology has been used in a variety of contexts, including military, government, and business services [14; 15; 16]. The military's use of SC technology stems from the need to identify terrorist transmitters, design obstructing emitters, and recover recorded waveforms as part of electronic warfare and threat assessment [17; 18; 19]. Modulation style, error-correcting code, and multiple antenna design are just a few of the many transmission characteristics used by modern industrial transmitters to optimize data rate and bandwidth utilization while preserving a targeted level of service quality [20; 21]. Each terminal in the broadcast network should be aware of all transmission settings.