INGR Roadmap Massive MIMO Chapter

Sun, Haijian; Ng, Chris T. K.; Huo, Yiming; Hu, Rose Qingyang; Wang, Ning; Chen, Chi-Ming; Vasudevan, K.; Yang, Jin; Montlouis, Webert; Ayanda, Dauda; Mishra, Kumar Vijay; Tekbıyık, Kürşat; Hussain, Nasir; Sahoo, Harish Kumar; Miao, Yang

doi:10.1109/fnwf55208.2022.00138

Cited by 6 publications

(4 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Invest in developing signal-processing algorithms that can efficiently handle the massive number of antennas involved in MIMO systems. This includes beamforming, channel estimation, and interference management [117][118][119][120].…”

Section: Technology Innovation and Standardizationmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

View full text Add to dashboard Cite

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning (ML), quantum communication, and reconfigurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and ML, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. We also address critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study maps out the current landscape and lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI technologies, we aim to illuminate the path forward in this rapidly evolving field.

show abstract

Section: Technology Innovation and Standardizationmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Invest in the research and development of signal processing algorithms that can efficiently handle the massive number of antennas involved in MIMO systems. This includes beamforming, channel estimation, and interference management [83,84].…”

Section: Challenges Possible Solutionmentioning

confidence: 99%

6G Networks and AI Revolution - Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2023

Preprint

View full text Add to dashboard Cite

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in mobile wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and the key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning, quantum communication, and re-configurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and machine learning, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. This paper also addresses critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study not only maps out the current landscape but also lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI(Artificial Intelligence) technologies, we aim to illuminate the path forward in this rapidly evolving field.

show abstract

“…A large number of users are served simultaneously by the base station. A comparison between MU-MMIMO and SU-MMIMO is given in Table I [27], [28]. The base station in MU-MMIMO uses beamforming to improve the signal-tonoise ratio at the mobile handset.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, SU-MMIMO uses spatial multiplexing to improve the spectral efficiency in the downlink and uplink. The comparison between beamforming and spatial multiplexing is given in Table II [27], [28]. The total transmit power of SU-MMIMO using uncoded QPSK versus MU-MMIMO using M -ary QAM is shown in Table III.…”

Section: Introductionmentioning

confidence: 99%

New Results on Single User Massive MIMO

Vasudevan¹,

Kota²,

Kumar³

et al. 2023

Preprint

View full text Add to dashboard Cite

Achieving high bit rates is the main goal of wireless technologies like 5G and beyond. This translates to obtaining high spectral efficiencies using large number of antennas at the transmitter and receiver (single user massive multiple input multiple output or SU-MMIMO). It is possible to have a large number of antennas in the mobile handset at mm-wave frequencies in the range 30 − 300 GHz due to the small antenna size. In this work, we investigate the bit-error-rate (BER) performance of SU-MMIMO in two scenarios (a) using serially concatenated turbo code (SCTC) in uncorrelated channel and (b) parallel concatenated turbo code (PCTC) in correlated channel. Computer simulation results indicate that the BER is quite insensitive to re-transmissions and wide variations in the number of transmit and receive antennas. Moreover, we have obtained a BER of 10 −5 at an average signal-tointerference plus noise ratio (SINR) per bit of just 1.25 dB with 512 transmit and receive antennas (512 × 512 SU-MMIMO system) with a spectral efficiency of 256 bits/transmission or 256 bits/sec/Hz in an uncorrelated channel. Similar BER results have been obtained for SU-MMIMO using PCTC in correlated channel. A semi-analytic approach to estimating the BER of a turbo code has been derived. Index Terms-Single user massive multiple input multiple output (SU-MMIMO), Rayleigh fading, serially concatenated turbo code (SCTC), parallel concatenated turbo code (PCTC), spectral efficiency (SE), signal-to-interference plus noise ratio (SINR) per bit, spatial multiplexing, bit-error-rate (BER).

show abstract

INGR Roadmap Massive MIMO Chapter

Cited by 6 publications

References 16 publications

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

6G Networks and AI Revolution - Exploring Technologies, Applications, and Emerging Challenges

New Results on Single User Massive MIMO

Contact Info

Product

Resources

About