About this Research Topic
Signals are used to quantify real-world physical quantities in science and engineering and ex-change information in communication networks. Hence, studying and analyzing related systems requires appropriate signal and system modeling to understand the theoretical performance and design suitable practical systems. Theoretical statistical studies adopt mostly complex symmetrical (proper) Gaussian distribution as a convenient model for analysis with simplified computations thanks to its uncorrelated equal power components. An important step to move closer to the actual physical quantities data is done by dealing with complex asymmetric (improper) Gaussian signals, which relax the proper Gaussian signal assumptions and include the symmetric (proper) Gaussian signal as a special case.
Similar to data analysis, communication systems also used proper signals motivated by the associated optimal performance in point-to-point interference-free communication systems and the mathematical tractability. Nowadays, we are witnessing a tremendous growth of information ex-change and network deployments due to the continual increase of ubiquitous high-speed communication network requirements. Hence, it is imperative to spend generous efforts and rethink innovative solutions to boost the communication system performance. Adopting improper Gaussian signaling is a promising technique that has recently demonstrated significant performance improvement for several network configurations, such as multiuser interference networks. Also, it provides accurate models for communication systems that cause/suffer from signal imbalance. The realization of practical systems that can meet the theoretical performance can be achieved by appropriate design of adaptive asymmetrical discrete constellations. Designing new families of discrete constellations can be done by asymmetric signaling in time, space, stochastic and geometrical domains. In regards to system implementations, it is necessary to develop appropriate signal processing schemes that are compatible with systems dealing with improper (asymmetric) signals. Specifically, several signal processing domains should be considered, such as estimation, detection, system identification, feature extraction, pattern recognition etc.
This special issue is devoted to studying the theoretical impact of improper Gaussian signaling on communication networks based on fundamental information theory studies, and realize practical systems using asymmetric discrete constellation based on appropriate signal processing techniques. High-quality technical paper submissions reporting on original algorithmic, theoretical, numerical, and experimental results are welcome. Exceptional survey/tutorial-like papers may also be considered.
The themes of interest include, but are not limited to:
• Improper and asymmetric signals in communication networks: cellular networks, cognitive radios, device-to-device communications, full-duplex systems etc.
• Interference management techniques using improper and asymmetric signals.
• Improper and asymmetric signals for physical layer security systems.
• Inherent and imposed impropriety in communication systems, such as hardware impairments and mitigation techniques.
• Widely linear signal processing for asymmetric signaling such as: equalization, estimation, filtering, precoding, detection etc.
• Improper Gaussian signals in non-orthogonal multiple access systems.
• Asymmetric discrete constellation design: probabilistic shaping, geometric shaping, asymmetric time-sharing and hybrid shaping schemes.
• Multi-agent distributed systems with improper and asymmetric signals.
• Asymmetric constellation design via machine learning techniques.
• Resource allocation for multiple users employing asymmetric signaling in communications networks.
• Cross-layer design for communication networks operating with asymmetric signals
• Asymmetric signals and reconfigurable intelligent surfaces for communication networks
• Caching and asymmetric signaling in communication networks
• Asymmetric signal experimental testbed and improper signal measurements.
Similar to data analysis, communication systems also used proper signals motivated by the associated optimal performance in point-to-point interference-free communication systems and the mathematical tractability. Nowadays, we are witnessing a tremendous growth of information ex-change and network deployments due to the continual increase of ubiquitous high-speed communication network requirements. Hence, it is imperative to spend generous efforts and rethink innovative solutions to boost the communication system performance. Adopting improper Gaussian signaling is a promising technique that has recently demonstrated significant performance improvement for several network configurations, such as multiuser interference networks. Also, it provides accurate models for communication systems that cause/suffer from signal imbalance. The realization of practical systems that can meet the theoretical performance can be achieved by appropriate design of adaptive asymmetrical discrete constellations. Designing new families of discrete constellations can be done by asymmetric signaling in time, space, stochastic and geometrical domains. In regards to system implementations, it is necessary to develop appropriate signal processing schemes that are compatible with systems dealing with improper (asymmetric) signals. Specifically, several signal processing domains should be considered, such as estimation, detection, system identification, feature extraction, pattern recognition etc.
This special issue is devoted to studying the theoretical impact of improper Gaussian signaling on communication networks based on fundamental information theory studies, and realize practical systems using asymmetric discrete constellation based on appropriate signal processing techniques. High-quality technical paper submissions reporting on original algorithmic, theoretical, numerical, and experimental results are welcome. Exceptional survey/tutorial-like papers may also be considered.
The themes of interest include, but are not limited to:
• Improper and asymmetric signals in communication networks: cellular networks, cognitive radios, device-to-device communications, full-duplex systems etc.
• Interference management techniques using improper and asymmetric signals.
• Improper and asymmetric signals for physical layer security systems.
• Inherent and imposed impropriety in communication systems, such as hardware impairments and mitigation techniques.
• Widely linear signal processing for asymmetric signaling such as: equalization, estimation, filtering, precoding, detection etc.
• Improper Gaussian signals in non-orthogonal multiple access systems.
• Asymmetric discrete constellation design: probabilistic shaping, geometric shaping, asymmetric time-sharing and hybrid shaping schemes.
• Multi-agent distributed systems with improper and asymmetric signals.
• Asymmetric constellation design via machine learning techniques.
• Resource allocation for multiple users employing asymmetric signaling in communications networks.
• Cross-layer design for communication networks operating with asymmetric signals
• Asymmetric signals and reconfigurable intelligent surfaces for communication networks
• Caching and asymmetric signaling in communication networks
• Asymmetric signal experimental testbed and improper signal measurements.
Keywords: Improper Gaussian signaling, Asymmetric discrete constellations, Wireless networks, Widely linear processing, Data analysis
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