IRS, LIS, and Radio Stripes-Aided Wireless Communications: A Tutorial

• Autor(a) principal: Gashtasbi, Ali
• Data de Publicação: 2022
• Outros Autores: Silva, Mário Marques da, Dinis, Rui
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/11144/5722
• topic: IRS; LIS; RS; 6 G

This is a tutorial on current techniques that use a huge number of antennas in intelligent re‑ flecting surfaces (IRS), large intelligent surfaces (LIS), and radio stripes (RS), highlighting the similar‑ ities, differences, advantages, and drawbacks. A comparison between IRS, LIS, and RS is performed in terms of the implementation and capabilities, in the form of a tutorial. We begin by introducing the IRS, LIS, and RS as promising technologies for 6 G wireless technology. Then, we will look at how the three notions are applied in wireless networks. We discuss various performance indicators and methodologies for characterizing and improving the performance of IRS, LIS, and RS‑assisted wireless networks. We cover rate maximization, power consumption reduction, and cost implemen‑ tation concerns in order to take advantage of the performance increase. Furthermore, we extend the discussion to some cases of emerging use. In the description of the three concepts, IRS‑assisted communication was introduced as a passive system, considering the capacity/data rate, with power optimization being an advantage, while channel estimation was a challenge. LIS is an active compo‑ nent that goes beyond massive MIMO; a recent study found that channel estimation issues in IRS had improved. In comparison to IRS, capacity enhancement is a highlight, and user interference showed a trend of decreasing. However, power consumption due to utilizing power amplifiers has restrictions. The third technique for increasing coverage is cell‑free massive MIMO with RS, with easy deployment in communication network structures. It is demonstrated to have suitable energy efficiency and power consumption. Finally, for future work, we further propose expanding the con‑ versation to include some cases of new uses, such as complexity reduction; design and simulation with LDPC code could be a solution to decreasing complexity.