Dirty paper coding may help achieve cleaner, faster communications in future tech

Calls drop, emails bounce, the text is still sending. Information sent via wireless channels is subject to uncontrollable environmental conditions that can delay or halt the communication. With the advent of 6G technology, there may be a way to exert more control, according to Radwa Sultan, assistant professor of electrical and computer engineering at Manhattan College.

Sultan and her international team examined how reconfigurable intelligent surfaces (RISs) and dirty paper coding, a telecommunications technique that involves precoding data to negate interferences, can work together to achieve highly efficient data transmission with maximum capacity. The researchers published their results on April 29 in Intelligent and Converged Networks at DOI: https://doi.org/10.23919/ICN.2022.0004.

“RISs challenge the conventional wisdom that the wireless propagation environment is uncontrollable,” Sultan said. RISs are smart, dynamically reflective arrays that can strengthen signals by duplicating them or routing them around various barriers. “They can add an additional and controllable phase response to the initial signal, which can help in controlling the overall propagation through the wireless environment.”

Wireless propagation can distort or scatter the transmitted signal, resulting in multiple copies of the signal arriving at the receiver with different delays or conditions, making them difficult to decode. According to Sultan, this is particularly problematic in multiple users, multiple access and broadcast channels.

“In this paper, we investigated the use of RISs to improve the dirty paper coding rate, or capacity, of a multi-user, multiple-input-multiple-output system,” Sultan said.

The researchers simulated a communications system comprising a RIS, a base station and mobile users.  They employed a capacity-achieving dirty paper precoding scheme at the transmitter, coding the signal to protect the information from interference, and proposed an optimization scheme for transmission. This scheme iteratively optimizes either the transmission conditions or the RIS reflection configurations. Since the links between the RIS and the users, as well as the base station and the users, vary, the alternating optimization may help mitigate unfavorable variables, resulting in a cleaner, more efficiently delivered message.

“Numerical simulation results demonstrated that the proposed technique can be used to effectively improve the sum rate capacity compared to benchmark schemes,” Sultan said. “The RIS increases the transmission diversity gain — meaning it varies how the signal is sent without degrading it — allowing for the achieved rate.”

The researchers plan to continue examining RISs and how they might be applied to advance communications.

“Deploying RISs in wireless transmission is a new, promising technique that will help achieve high-performance gains and will play a vital role in next-generation wireless communication networks,” Sultan said.  

Other contributors include Mohamed A. ElMossallamy and Han Zhu, Electrical and Computer Engineering Department, University of Houston; Karim G. Seddik, Electronics and Communications Engineering Department, American University in Cairo; and Geoffery Ye Li, Department of Electrical and Electronic Engineering, Imperial College London. Zhu is also affiliated with the Department of Computer Science and Engineering, Kyung Hee University.

The National Science Foundation partially supported this research.

The paper is also available on SciOpen (https://www.sciopen.com/home) by Tsinghua University Press.

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About Intelligent and Converged Networks 

Intelligent and Converged Networks is an international specialized journal that focuses on the latest developments in communication technology. The journal is co-published by Tsinghua University Press and the International Telecommunication Union (ITU), the United Nations specialized agency for information and communication technology (ICT). Intelligent and Converged Networks draws its name from the accelerating convergence of different fields of communication technology and the growing influence of artificial intelligence and machine learning.

About SciOpen 

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