Telecommunications
Engineering, Financing, Medical care

Design of statistical signal processing for wirelesscommunications
Division of Electrical, Electronic and Infocommunications Engineering, Graduate School of Engineering
Assistant Professor Takumi Takahashi
https://researchmap.jp/takumi_takahashi?lang=en

Telecommunications

Abstract
Large multi-user multi-input multi-output (MIMO) technology (Fig. 1),
which spatially multiplexes information streams simultaneously transmitted
by wireless terminals, is one of the essential physical layer technologies!"#$%
to meet the ever-increasing demand for wireless connectivity. However,to realize this technology, it is necessary to separate (detect) the spatiallymultiplexed signals at the base station receiver, and it is vital to develop
advanced uplink signal detection algorithms. In the present study, we
designed a beamforming algorithm based on long-term channel statistics
according to the spatial arrangement of wireless terminals, and a novelsignal detection algorithm based on belief propagation (BP) that operates
in the beam domain after fully-digital beamforming.

in the real world will be the key to connect the two spaces at a high level,and this study is the creation of such a foundation. The proposed framework is based on Bayesian inference, and it is compatible with the use ofprior knowledge obtained from artificial intelligence (AI)-related technologies and the embedding of learning techniques into algorithms; hence,currently, we are also working on integration with machine learning.

!"#$!%&'$"(%()*+▍ Background & Results
In the vision of the future society proposed by Society 5.0, wirelesscommunications are positioned as an information infrastructure that highly
connects the real and virtual worlds. In particular, it is essential to upgrade
the uplink communications that aggregate real-world informationfrom(差し替え)
主要図表2
countless sensor terminals. The conventional exclusive allocation of radio resources to each device has its limitations, and interference tolerant
non-orthogonal multiple access (NOMA) is crucial for the next generation
wireless communication system. The key to success is a receiver designthat efficiently eliminates non-orthogonal interference and maximizes system performance.
In the case of large multi-user MIMO systems, advanced signal processing is required to detect the received multidimensional signals withlow computational cost. The BP methods developed in the context ofphysics and (thermo-) statistical mechanics have attracted attention aspromising candidates; however, it is difficult to create the ideal stochastic
conditions for these algorithms in real wireless communications, and thishas been a major obstacle to their practical application.
The contribution of this study is that we have incorporated this elaborate
algorithm into the engineering problem, i.e., large MIMO detection, proposed an algorithm structure that can be practically used under non-ideal
conditions, and paved the way for its utilization as a physical layer technology for 6G and beyond. Specifically, we designed a layered BP algorithm
that is appropriate for the structure of beam-domain channels reduced
in dimensionality by digital beamforming, and succeeded in realizing accurate signal detection under correlated fading environments. Computer
simulations demonstrate that the performance approaching that of existinghigh-complexity detection state-of-the-art counterpart can be achieved
with only a few percent of computational cost (Fig. 3).

,-#$,&'.$-/0)12'+(Fig.1: Illustration of large multi-user MIMO

Cyber space
Big data
Artificial Intelligence
Wireless spaceSensor
information

High-value
information

Flexibly connecting
the two spaces
with wirelesscommunications

Automatic driving
toward a society withzero accidents

Providing and sharing
the information you need,when you need it

Smart factory with robots
and mission-critical
Internet of Tings

Physical space

Fig.2: Cyber-physical fusion▍ Significance of the research and Future perspective
Cyber-physical fusion is a future framework that connects cyber space(virtual world) and physical space (real world) and provides an informationinfrastructure to solve all social problems such as poverty and hunger
through efficiency, optimal allocation, and future prediction based on aggregated big data (Fig. 2). In this system, wireless communication technologies that can accommodate a large number of wireless/sensor terminals

Fig.3: Comparison of performance and complexity

P a t e n t US11309991, US11627485
Takahashi, Takumi; Tölli, Antti; Ibi, Shinsuke et al. Low-complexity large MIMO detection via layered belief propagation in beam domain, in IEEE
Transactions on Wireless Communications. 2022, 21(1), 234-249. doi: 10.1109/TWC.2021.3094970
Takahashi, Takumi; Iimori, Hiroki; Ando, Keigo et al. Bayesian receiver design via bilinear inference for cell-free massive MIMO with low-resolution ADCs, inTr e a t i s eIEEE Transactions on Wireless Communications. 2023, 22(7), 4756-4772. doi: 10.1109/TWC.2022.3228326
Shirase, Daichi; Takahashi, Takumi; Ibi, Shinsuke et al. Deep unfolding-aided gaussian belief propagation for correlated large MIMO detection, in Proc.
IEEE Global Communications Conference, Taipei, Taiwan. 2020, 1-6. doi: 10.1109/GLOBECOM42002.2020.9348087
UR
L https://www.researchgate.net/profile/Takumi-Takahashi-4
K e y w o r d wireless communications, signal processing, bayesian statistics, coding theory, information theory