This paper presents an inspection and review of wired and wireless channel equalization techniques and their existing hardware implementations in terms of features, similarities, and differences. The authors begin with the theory behind channel equalization followed by techniques, and the technological realizations for achieving the proper filter in response to variations of the channel. Included in both the techniques and realizations are the rebirth of the use of artificial intelligence as a self-learning filter for the weights to use by the filtering structure of channel equalizers. These equalizers were compared, contrasted, and their key differentiation was identified. It was found that gaps such as complexity and convergence time are potential areas for extending the performance and limits of existing channel equalizers.
As the world advances into 5G networks, significant scientific research accomplishments are being conducted for a communication system that could further enhance the current limit of data transmission capacity. Currently, the communication systems with the highest data rate are optical fiber systems. Due to the recent advancement of coherent optical fiber communications by exploiting time, wavelength, phase, amplitude, polarization, and space, optical engineering can break the petabit barrier data rate. Thus, coherent optical fiber communications is a hot topic due to its very high data rate that could be applied or a requirement in 5G and big data analytics. This paper focuses on a comparative survey of the current applied fundamental techniques in fiber communication channels. These fundamental techniques that could be further studied and exploited to increase the bandwidth performance, decrease the error rate and energy consumption are coding, multiplexing, and equalization. At the end of this paper, a comparative result is discussed to explain the difference among the current techniques in the literature for the optical engineering community to improve collective coding, multiplexing, and equalization in coherent fiber systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.