## 3 Challenges and Related Recommendation
### Fundamental Theories Challenges
Since the majority of modules focus on addressing the greatest a posteriori estimate problem, they can be integrated into a cohesive Bayesian system by leveraging their identical features, hence enhancing the efficiency of the iterative receiver. Given the serial nature of the signal circulation, one alternative method is to consider many modules collectively, treating the end result as the target for joint processing, including joint detection and decoding [64]. Figure 10 illustrates an example [65] of the instance of sparse code multiple access (SCMA) encoding for \(J=6\) and \(K=4\), employing quadrature phase shift keying (QPSK) modulation, with a modulation magnitude of 2 for QPSK. Every user is allocated two assets based on the codebook selected. The \(J\) codewords are, thereafter, transferred using \(K\) supplies. Each SCMA codeword takes only a portion of the supply. The whole configuration of the SCMA might be depicted by a \(K\times J\) factor graph matrix. A component that is greater than zero in the \(k\)-th line and \(j\)-th field of the factor graph matrix indicates that the asset \(k\) is allocated to user \(j\). Every asset is utilized by \(N_{\mathrm{u}}\) users, and the communication from each user is conveyed by \(N_{\mathrm{r}}\) assets. Reliable unified equipment design and accompanying implementations are crucial for meeting many realistic purposes based on cyclic or cooperative baseband processing. In pre-6G telecommunication networks, the layout and construction of each module are segregated, and the absence of system-level design considerations leads to increased hardware asset expenditures. To enhance the adaptability, compatibility, and hardware effectiveness of 6G baseband handling executions, the VLSI-DSP technique [67], which includes retiming, bending, and unfolding, may be employed to create a solid design featuring fixed handling aspects, improved network interconnections, and iterative timing timetables. The intricate and varied uses of 6G networks of communication necessitate specialized electronic architecture automated solutions for baseband handling, which can reduce the entry obstacles for circuit designs across numerous scenarios and fulfil client requirements. An effectively developed automation tool can autonomously produce the circuit architecture according to the customer's quality specifications. Utilizing the unified Bayesian system, the majority of the computation modules may be defined to enhance the auto-generation technique, hence establishing a design space for optimizing hardware attributes [68; 69]. Figure 11 illustrates the automated development of hardware architectures, it shows a hardware architectures auto generation where the F represents the latency and throughput while I, II, and III refer to a different type of the polar encoders. Standardization of polar codes for use in improved mobile broadband management channels has p  
Figure 10: Example of SCMA encoding procedure. of other potential users. For the purpose of automating the generation of Verilog HDL files for the hardware implementation of F\({}_{\text{I(N,M)}}\), F\({}_{\text{II(N,M)}}\), and F\({}_{\text{III(N,H)}}\), a Python compiler called the Polar Compiler was employed in the study [68]. The compiler files are available on GitHub [70]. AI can assist in the discovery of design spaces with complex needs. It can also assist in identifying the compensatory parameters induced by estimation, quantization methodologies, and iterative techniques in the automated hardware design process [71].