Reconfigurable Intelligent Surfaces(RIS’s) for Future Wireless Networks
Introduction:
In recent months, researchers have been working tirelessly to solve one of the long outstanding and unsolved wireless channel problems. For the longest time, we have not been able to control the propagation environment in the wireless channel. This uncertain environment made it expensive and complex to implement wireless communication systems. It has also led to the degradation of the signals due to the precarious conditions of these channels. RISs have emerged with the promise of achieving very high spectrum and energy efficiency for future wireless networks. These RISs integrate a large number of low-cost passive reflecting elements/ software-controlled metasurfaces that reflect the incident signal from the source to the destination, especially where the direct path is weak. The RIS will manipulate the properties of the incident wave, such as phase and amplitude, and then reflect this manipulated incident wave to the desired destination.
Some three examples of recent works:
Marco di Renzo, Nemanja Stephani Perovic, and Mark F Flanagan, in their work “Channel Capacity Optimization Using Reconfigurable Intelligent Surfaces in Indoor mmWave Environments,” propose two optimization schemes that exploit the customizing capabilities of the RIS reflection elements to enhance the channel capacity. These are:
i) optimization scheme uses only the adjustability of the RIS reflection elements
ii) optimization scheme jointly optimizes the RIS reflection elements and the transmit phase precoder
From their work, they achieved significant channel capacity gains from systems with a massive number of IRS elements.
Mihai-Alin Badiu and Justin P. Coon, in their work, “Communication Through a Large Reflecting Surface With Phase Errors, “come to terms with difficulty in obtaining perfect phase estimation or high-precision configuration of the reflection phases. They have been able to show that the composite channel through an IRS with phase errors is equivalent to a point-to-point channel with Nakagami fading channel. From there work, and with these phase error, they were able to show that average SNR and the diversity order both increase. They showed that performance is robust against phase error.
Sha Hu and Fredrik Rusek have gone further in their work, “Spherical Large Intelligent Surfaces,” propose the extension of the LIS to 3-D and deploy them as spherical surfaces to achieve broad coverage, simple positioning techniques and flexible deployments as reflectors. In there analytics, they show that the spherical yields higher received signal strength(RSS) when a terminal moves around and lower positioning CRLB compared to planar IRS. They can also be applied as a low-cost controllable reflector.
To be continued: …
