## 5 RIS Implementation Structures
### Novel Active RIS Structure and Signal Model  
Active RISs are considered novel implementation structures due to their numerous benefits and applications in many communication areas. As opposed to passive RISs  
Figure 5: RIS structures based on energy consumption (**a**) An active RIS implementation (**b**) Existing passive RIS impementation.  
that reflect signals without amplification, they can further amplify the reflected signals. Active RISs can avoid the drawbacks of passive RIS, especially the multiplicative fading phenomenon, as active RISs can enhance the reflected signals at the expense of extra power consumption, unlike passive RISs that only reflect signals without amplification. In addition, active RISs can also reflect incident signals with adjustable phase shifts, similar to passive RISs. The additionally integrated active reflection-type amplifier, which can be realized by different existing active components, such as current-inverting converters, asymmetric current mirrors, or even some integrated circuits, is the key component of an active RIS element.  
The drawback of active RISs is that they consume more power to amplify reflected signals because they utilize active components. The thermal noise created by active RIS elements cannot be ignored as easily as it can be with passive RISs. The authors in [90] developed an active RIS signal model that was validated by experimental measurements. A point-to-point multiple-input single-output (MISO) wireless system in which an Access Point (AP) serves a single-antenna user with M antennas is developed and analyzed. An intelligent reflective surface (IRS) made of N passive elements is mounted on a surrounding wall to aid the AP-user communication/power transfer to improve connection performance. The IRS, equipped with a smart controller, can modify the phase shift of each reflecting element dynamically based on the propagation environment learned through periodic monitoring via the same passive array (when not reflecting). The IRS controller coordinates the transition between two operating modes: receiving mode and environment sensing mode. Finally, the sum-rate maximization problem for active RIS-assisted multiple-input multiple-output (MIMO) systems was framed using this paradigm. A precoding solution was developed and presented a joint transmit beamforming and reflect precoding algorithm that solves this problem. The results demonstrated that existing passive RISs could only achieve a small sum-rate gain of 3% in a typical wireless system. However, the suggested active RISs achieved a considerable sum rate gain of 108 percent, thereby avoiding the \"multiplicative fading\" phenomenon present in passive RISs [42].  
In many industrial internet-of-things (IoT) applications, such a system can be used to facilitate wireless information and/or power transfer. Therefore, the authors also optimized the (active) transmit beamforming at the AP and (passive) reflect beamforming by the phase shifters at the IRS to achieve the maximum signal power received at the user. The authors assumed that the user receives superposed signals from the AP-user (direct) link and the IRS-user (direct) link.