## 1 Introduction  
The Internet of Things (IoT) has become an integral part of human life with various applications in industry, manufacturing, agriculture, healthcare, etc. The development of 5G wireless communications enables many new devices to communicate and to be able to make autonomous decisions by deploying diverse technologies and connecting massive devices [1; 2; 3]. The 5G network supports and targets two main services for IoT applications such as ultra-Reliable Low-Latency Communications (uRLLC) and massive Machine-Type Communications (mMTC) [4]. uRLLC is a new class of performance communications that focuses strictly on the highest possible reliability and enables latency as low as 1 ms, since it concentrates on supporting mission-critical applications such as intelligent transportation and industry automation [2; 5]. mMTC focuses mainly on efficiently transmitting a low data amount intermittently to and from devices that require wide area coverage and a long battery life, which can be up to thousands of devices such as wearable or smart applications and sensors in the IoT [6]. In order to be efficient, short-length transmissions or short-packet transmissions should be used certainly for both uRLLC and mMTC in their applications [1]. Furthermore, compared to the infinite packet transmission system, short-length packet transmission is considered as a foundation of Physical Layer Security (PLS) problems in 5G and IoT applications to ensure the robustness of artificial noise or self-jamming techniques [7]. Last but not least, as 5G has gone to the final stage, 6G hasreceived much interest from the research community because it is targeted to support more diversified applications. Therefore, both the uRLLC and mMTC techniques should be explored deeply in order to fully support short-packet communications, not only to provide an efficient data transmission, but also to ensure communication reliability [8; 9]. Since the deployment of 5G will lead to a network expansion by offering a platform for connecting a large number of IoT devices, it requires new fundamental solutions for sharing the spectrum efficiently. Full-Duplex (FD) transmission, simultaneously transmitting and receiving data through the same resource (time and frequency), is a promising technique for 5G and Beyond wireless networks because it can \"theoretically\" double the spectral efficiency, compared to the traditional Half-Duplex (HD) method such as Time Division Duplex (TDD) or Frequency Division Duplex (FDD) [10]. However, to achieve the doubled spectral efficiency in practice for this FD transmission, the Self-Interference (SI) component must be cancelled close to the noise floor level, which is not an easy task due to the high power, which may reach up to 120 dB in the real communication networks and then strongly disturb the reception behaviour [11]. Therefore, SI cancellation would play the most critical role in implementing FD communication systems in both academia [12; 13] and industry [14; 15]. Nevertheless, the use of an FD transmission with good control of SI can provide many advantages to modern wireless communications systems, both in terms of spectral efficiency, as well as reliability and security through the use of self-jamming techniques [16]. In order to cancel the SI component to a reasonable level, many techniques have been proposed such as the passive technique with Radio Frequency (RF) cancellation (beamforming, antenna decoupling or isolation, cross-polarisation, etc.) [17; 18; 19] or active techniques with analogue cancellation [20; 21] (analogue filter, etc.) and digital cancellation [22]. Although the SI component's cancellation has already been implemented at the RF and analogue level, in order to cancel it to an acceptable level, a large amount of the residual SI component still needs to be continuously cancelled in the digital domain. Therefore, a Digital Self-Interference Cancellation (DSIC) process has been applied to estimate the residual SI and cancel it from the received signal.