## 1 Introduction  
The increased demand for high speed data transfers, in conjunction with the limited availability of the licensed spectrum, has fueled the explosive expansion of the radio communications market in recent years, and this progress is expected to accelerate over the coming decade. The deployment of adaptive transmissions is indispensable in order to meet this demand [1, 2]. Waveform recognition (WR) is the process of analyzing a collected waveform in order to investigate its properties. It is the central operation of adaptive radios, which modify the broadcast parameters in response to channel state information. This optimizes the service level while reducing the power consumption and boosting the information rate during transmissions. The concept of WR is currently being utilized in a vast array of circumstances, including in the armed services, government, and private industry [3]. The tactical utilization of WR was the inspiration for its advancement, as threat evaluation and digital warfare require the recognition of the broadcast parameters of an intercepted waveform to differentiate enemy emitters, produce blocking waves, and retrieve the captured signal [4; 5]. Examples of the broadcast characteristics include modulation and coding types, information rate, and carrier frequency. The broadcasters of the majority of current industrial applications, such as cellular and microwave communications systems, select their parameters from a collection of options available to both the transmitting and receiving sites. Due to the fact that the receiver is unaware of the precise parameters that were applied during transmission, the receiving station is required to implement various kinds of WR mechanisms to secure the truthfulness of the demodulated information. Cognitive radios provide another illustration of the importance of WR, as they enable unauthorized individuals to send information over channels that are already being utilized by other lawful customers. A WR method is a critical component of the architecture of cognitive radios, and its principal intent is to evaluate the type of parameters available in the collected waveforms [6; 7]. This allows cognitive radios to transmit without interfering with customers who are presently accessing their channels. Government bodies also employ WR for spectrum surveillance to guarantee conformity to radio licensing requirements. This ensures that crucial organizations, such as security services, firehouses, navigation stations, and armed forces, have access to powerful communication systems that are immune to environmental interference [8; 9; 10]. In general, the majority of modern wireless systems need to transmit massive volumes of data via wideband frequency selective links. In such environments, it is crucial that undesirable inter-symbol disturbance is not incorporated into the system design. Multicarrier transmission systems have been demonstrated to be an appropriate solution to mitigating the detrimental effects of such channels [1; 2; 11]. The fundamental idea behind such setups is to divide a high speed serialized data flow into many simultaneous low speed sub-flows. Each sub-flow is processed by a single sub-carrier, resulting in a lower susceptibility to inter-symbol disturbance and, as a consequence, a simplified equalization mechanism. Meanwhile, multiple-input multiple-output technology has been developed as a further advance in the development of wireless communication systems. This is because of the significant performance benefits in linking dependability, data throughput, and broadcast distance, as well as the ease with which it is implemented. It comes as no surprise that several of the world's current communications systems have incorporated the combination of multicarrier and multiple-input multiple-output technologies. Examples involve digital audio and video broadcast systems, wireless local area connections, satellite and microwave systems, as well as the fourth and fifth generations of cellular communications [12].