Over the past decades, the demand for wireless data traffic is dramatically increasing. The use of mmWave has been widely adopted and Teraherz communication has been envisioned as the key technology in 6G network to provide large bandwidth. However, wireless signals experience large attenuation loss in both frequency ranges and the line-of-sight link is vulnerable to blockage effects. Massive MIMO has been applied in these bands to provide significant beamforming gain. However, this may lead to unaffordable power consumption and hardware complexity. Reconfigurable intelligent surface (RIS) has emerged as a sustainable solution to enhance wireless connectivity. They are particularly appealing due to the low power consumption as an array of low-cost passive reflecting elements, which can be adaptively adjusted to reconfigure both the amplitude and phase of the incident signals without the need of radio frequency (RF) chains. RIS enabled wireless communication has become a hot research topic due to their ability to reconfigure the wireless propagation environment and simple deployment.
To unleash the full potential of RIS enabled massive MIMO systems, accurate channel estimation (CE) is an essential prerequisite. Since no active elements are used in the RISs, CE becomes a challenging task due to the large array size requiring very high pilot overhead. Moreover, in both mmWave and THz bands, beamforming gain is critical to overcome the interference and range limitations. Though the investigation of channel estimation in the RIS aided mmWave massive MIMO systems has recently attracted some attention, the application of RIS in the THz band is still at early development stage. Therefore, the channel estimation problems, the optimization of RIS enabled channel, transceiver design, and high-power consumption and complexity existing in the beamforming must be solved.
Original papers are sought in the following areas:
1) Channel estimation for RIS aided massive MIMO systems in mmWave and/or THz bands
3) Machine learning based channel estimation and transmission design in RIS aided massive MIMO systems
4) Beamforming for RIS-enabled massive MIMO systems
5) Optimisation of the RIS-enabled channel usage
6) Robust design based on hardware impairment and/or imperfect channel knowledge
7) Association and coordination among RISs, base stations, access points and users
8) Resource allocation and interference management in RIS aided massive MIMO systems
9) Integration of RIS aided massive MIMO systems in emerging wireless applications (mobile edge computing, energy harvesting, UAV, next generation multiple access, physical layer security, etc.)
Keywords:
Reconfigurable intelligent surface (RIS), Massive MIMO Channel estimation, Hybrid Precoding, Transmission Design, Resource Allocation
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Over the past decades, the demand for wireless data traffic is dramatically increasing. The use of mmWave has been widely adopted and Teraherz communication has been envisioned as the key technology in 6G network to provide large bandwidth. However, wireless signals experience large attenuation loss in both frequency ranges and the line-of-sight link is vulnerable to blockage effects. Massive MIMO has been applied in these bands to provide significant beamforming gain. However, this may lead to unaffordable power consumption and hardware complexity. Reconfigurable intelligent surface (RIS) has emerged as a sustainable solution to enhance wireless connectivity. They are particularly appealing due to the low power consumption as an array of low-cost passive reflecting elements, which can be adaptively adjusted to reconfigure both the amplitude and phase of the incident signals without the need of radio frequency (RF) chains. RIS enabled wireless communication has become a hot research topic due to their ability to reconfigure the wireless propagation environment and simple deployment.
To unleash the full potential of RIS enabled massive MIMO systems, accurate channel estimation (CE) is an essential prerequisite. Since no active elements are used in the RISs, CE becomes a challenging task due to the large array size requiring very high pilot overhead. Moreover, in both mmWave and THz bands, beamforming gain is critical to overcome the interference and range limitations. Though the investigation of channel estimation in the RIS aided mmWave massive MIMO systems has recently attracted some attention, the application of RIS in the THz band is still at early development stage. Therefore, the channel estimation problems, the optimization of RIS enabled channel, transceiver design, and high-power consumption and complexity existing in the beamforming must be solved.
Original papers are sought in the following areas:
1) Channel estimation for RIS aided massive MIMO systems in mmWave and/or THz bands
3) Machine learning based channel estimation and transmission design in RIS aided massive MIMO systems
4) Beamforming for RIS-enabled massive MIMO systems
5) Optimisation of the RIS-enabled channel usage
6) Robust design based on hardware impairment and/or imperfect channel knowledge
7) Association and coordination among RISs, base stations, access points and users
8) Resource allocation and interference management in RIS aided massive MIMO systems
9) Integration of RIS aided massive MIMO systems in emerging wireless applications (mobile edge computing, energy harvesting, UAV, next generation multiple access, physical layer security, etc.)
Keywords:
Reconfigurable intelligent surface (RIS), Massive MIMO Channel estimation, Hybrid Precoding, Transmission Design, Resource Allocation
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.