News

• The trend of using larger antenna arrays continues, but space constraints on user equipment (UE) in FR1 limit user capacity scaling. To address this, we propose UE-CoMIMO, a user-centric collaborative MIMO approach forming a virtual antenna array with multiple fixed or portable devices.

• The UE-CoMIMO system (256QAM, 100MHz bandwidth) offers impressive performance, including:

- Compliance with the 5G NR frame structure;

- A base station with 4 spatial atreams;

- A primary UE with 8 antennas (4 at 3.65 GHz and 4 at 7.65 GHz);

- A collaborative UE with 4 antennas for both frequency bands.

• For more details, please refer to the following paper. 

[ArXiv]  End-User-Centric Collaborative MIMO: Performance Analysis and Proof of Concept

As Guest Editors of IEEE Communication Magazine, along with Xingqin Lin, Jun Zhang, and Hadis Karimipour, we invite your original research submissions for our Special Issue on "Digital Twins and Artificial Intelligence in 6G".

Enhancing user experience in data speed and reliability is the focus of 5G and beyond networks. Innovations like wireless backhaul and relays are replacing traditional macro base stations. The article summarizes 5G features and ongoing 3GPP Release 18 developments related to intelligent EM entities like IAB, NCR, and RIS. It outlines the expected evolution of wireless networks in architecture, operations, and control signals.

• Active RIS-assisted MIMO-OFDM Prototype Conforming to the 5G New Radio Waveform:

- 4x4 MIMO-OFDM System (256QAM, 100MHz Bandwidth, 7.025GHz Carrier Frequency)

- 4 Transmit Antennas on Femtocell Base Station, 4 Receive Antennas on a Compact Phone (8cm x 15cm) 

- 4x4 Active RIS (13cm x 13cm)

• For more detailed information, please consult the following paper (Please note that the experiments in the paper were conducted at 3.5GHz, while the above demonstration operates at 7GHz) and demo video.

[IEEE Xplore], [Demo Video] Active RIS-Assisted MIMO-OFDM System: Analyses and Prototype Measurements

• In 6G, limited space in user equipment (UE) hinders the installation of additional antennas, limiting capacity scaling for end-users. To address this, we propose UE-CoMIMO, a collaborative MIMO framework that groups devices to create virtual antennas.

• [IEEE Xplore] MIMO Evolution toward 6G: End-User-Centric Collaborative MIMO

• [RWS-230111] Device collaborative Tx and Rx, MediaTek Inc., 3GPP RAN-Release 19 Workshop (2023-06-15 - Taipei)

• 8-spatial-stream MIMO on compact terminals operating at mid-high frequency (7.045GHz) achieves a spectral efficiency of 56 bps/Hz in an indoor open environment, utilizing a 100MHz bandwidth and 1024QAM modulation. 

• 3.5 times higher than the current 4x4 MIMO spectral efficiency of 5G NR at the 3.5GHz frequency band, which is approximately 15 bps/Hz.

• 5G NR at 3.5 GHz

• 4T4R MIMO OFDM

• 4 patch antennas at BS, 4 Rx antennas on a compact phone (8cm x 15 cm)

• 4x4 Hybrid Active-Passive RIS (16cm x 26cm)

• 5 dB increase in SNR and a 20% increase in spectral efficiency

•  Our paper "Overview of Deep Learning-Based CSI Feedback in Massive MIMO Systems" has been published in IEEE Transactions on Communications. In this paper, we give a detailed overview of the latest research on this topic.

• "AI for CSI Feedback Enhancement in 5G-Advanced" has been published in IEEE Wireless Communications. This paper focuses on how industry is using AI to improve feedback for communication systems, specifically as it relates to the new 5G-Advanced standard.

• Our proposed method, CsiNet, opens a new avenue  in the field of CSI Feedback by incorporating the use of Autoencoders. [Python & Matlab in GitHub]

• (RAN#94-e, Dec. 2021) In December 2021, 3GPP approved the Release-18 package at the RAN Plenary meeting. The package included a study item (RP-213599)-Artificial intelligence (AI)/machine learning (ML) for NR air interface. This study item will focus on three identified use cases, including CSI feedback, beam management, and positioning.

• MathWorks has included CsiNet in MATLAB 2022b toolbox (Aug. 2022).

• mmWave smartphone with two subarrays at the 28 GHz

• 5G NR Frame Structure with beam management (Rel-15) 

• 100 MHz channel width

• Modulations from QPSK to 256-QAM

• Fast antenna and beam switching (Fast-ABS) mechanism: Using the information of a single receiving array module to predict the receiving performance of other array modules. When the receiving module is blocked, Fast-ABS can quickly perform module and beam switching.

• 12x12 MIMO-OFDM based on 5G NR frame structure (Rel. 15)

• 12- Rx antennas in a compact smartphone for the 3.5 GHz

• 12-Tx spatial streams over 2 distributed BSs

• 100 MHz channel width

• 64-QAM

• Achieving 42.9 bps/Hz spectral efficiency on a 5.5 inch screens compact smartphone by using 

1) Precoding over two distributed BSs, 

2) Smart channel estimator with environment sensing,

3) AI-aided MIMO detector,

4) Joint MIMO detector and LDPC decoder (JDD)

• mmWave smartphone with two subarrays for the 28 GHz

• NR Frame Structure (Release 15)

• 100 MHz channel width

• From QPSK to 256-QAM

• Fast antenna and beam switching (Fast-ABS) mechanism

• Efficient and seamless connectivity under hand blockage

• mmWave antenna system in a smartphone for the 28 GHz

• NR Frame Structure (Release 15)

• 100 MHz channel width

• 256-QAM and 1204-QAM

• Fast beam tracking mechanism

• Support various performance measurement (e.g., EVM, SNR, throughput, beam pattern )

• 20 (or 16)-antenna array in the compact smartphone for the 3.5 GHz

• 16 spatial streams

• 100 MHz channel width

• 256-QAM for 20-antennas (or 64QAM for 16-antennas)

• 62.4 bps/Hz (or 49.7 bps/Hz) spectral efficiency on a compact smartphone with 5.5 inch screens

• 20-antenna array in the compact smartphone for the 3.5 GHz

• 14 spatial streams

• 100 MHz channel width

• 256-QAM

• 59.5 bps/Hz spectral efficiency on a compact smartphone with 5.5 inch screens

• 16-antenna array in the compact smartphone for the 3.5 GHz

• 12 spatial streams

• 100 MHz channel width

• 256-QAM

• 53.41 bps/Hz spectral efficiency