## 3 Related Works  
In light of the beneficial characteristics of RISs mentioned previously, many researchers have explored the potential benefits of RIS-aided systems in wireless networks. These benefits include reducing power consumption during transmission [10; 11; 12; 13; 14], improving spectra and EE [4; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26], and creating an unobstructed LoS [27; 28; 29; 30; 31; 32; 33; 34]. More specifically, the authors of [10] proposed an alternating optimisation approach for pieces of user equipment (UE) sensing based on their size and identified a trade-off in joint beamforming between sensing the target user size and the real communication operation. Under specific constraints, the authors in [11] jointly optimised the active beamforming vector at the access point (AP) and reflection beamforming at the RISs to maximise the received Signal-to-Noise Ratio (SNR) of a single user and the sum rate of multiple users, respectively. The authors of [12] employed joint beamforming to increase energy collecting and information transfer with uplink and downlink for Internet of Things (IoT) devices. Moreover, in [13], the authors proposed a hybrid networking structure that utilises cascaded and parallel RIS beamforming topology. The cascade alignment reduces path loss and improves multiplicative gain, while the parallel alignment boosts scattering signatures within the desired cluster. On the other hand, the authors of [14] employed the block denationalisation method to express the beamforming matrices of the BS and the users through the phase shifts of a RIS. Subsequently, they proposed a manifold method for enhancing beamforming optimisation by replacing the beamforming matrices of the BS and the users with their respective expressions. In order to improve EE and the coverage area, the authors of [15; 18; 20] used an unmanned aerial vehicle (UAV) with an RIS for downlink and uplink communication to assist the connection between the BS and UE; although this sounds very promising, the complexity and interference that the pieces of UE face are neglected. Furthermore, a RIS-aided multiple-input multiple-output (MIMO) system's communication spectrum optimisation and energy were characterised in [16; 17; 19; 24; 25], where the authors used active RF chains to optimise transmission power and reduce system delay. Additionally, the mmWave multiple-input single-output (MISO) system EE optimisation problem was addressed in [21; 22]. A swarm optimisation algorithm was used in [21] for RIS phase shifting to maximise the EE in the sine-cosine approach, while the authors of [22] used visible light communication technology to achieve the same objectives. The authors of [23; 26] optimised the EE and the bit error rate of a RIS-aided communication system by utilising the channel state information via compressive sensing techniques and a uniform planner array, respectively. The authors of [27; 30] provided a pathway of reflection that involved multiple hops over both active and passive RISs. Specifically, the active RISs have the ability to strategically amplify the reflected signal over the multi-reflection connection, thereby counteracting the significant loss of signal strength due to distance and optimisingenergy efficiency. In [28; 29; 31; 32; 33; 34], a multi-RIS approach is introduced in which all the used RISs are passive. The used approaches were designed to maximise the sum rate in mmWave systems and provide a direct LoS. In addition, Table 1 shows a comparison of the current state-of-the-art methods for the conventional T/R RIS and their achievement in providing wireless communication systems that have addressed and solved the need for higher reliability, lower delay, higher area coverage, less power loss, and higher system efficiency compared to the novel HRIS-DMA. Notation: All the parameters that are not defined inside the text are identified in Table 2, which presents the mutual design parameters.