8 research outputs found
A Transmit-Receive Parameter Separable Electromagnetic Channel Model for LoS Holographic MIMO
To support the extremely high spectral efficiency and energy efficiency
requirements, and emerging applications of future wireless communications,
holographic multiple-input multiple-output (H-MIMO) technology is envisioned as
one of the most promising enablers. It can potentially bring extra
degrees-of-freedom for communications and signal processing, including spatial
multiplexing in line-of-sight (LoS) channels and electromagnetic (EM) field
processing performed using specialized devices, to attain the fundamental
limits of wireless communications. In this context, EM-domain channel modeling
is critical to harvest the benefits offered by H-MIMO. Existing EM-domain
channel models are built based on the tensor Green function, which require
prior knowledge of the global position and/or the relative distances and
directions of the transmit/receive antenna elements. Such knowledge may be
difficult to acquire in real-world applications due to extensive measurements
needed for obtaining this data. To overcome this limitation, we propose a
transmit-receive parameter separable channel model methodology in which the
EM-domain (or holographic) channel can be simply acquired from the
distance/direction measured between the center-points between the transmit and
receive surfaces, and the local positions between the transmit and receive
elements, thus avoiding extensive global parameter measurements. Analysis and
numerical results showcase the effectiveness of the proposed channel modeling
approach in approximating the H-MIMO channel, and achieving the theoretical
channel capacity.Comment: Double column, 6 pages, 3 figures, 1 table, accepted by 2023 IEEE
Global Communications Conference (GLOBECOM 2023
Holographic MIMO Communications with Arbitrary Surface Placements: Near-Field LoS Channel Model and Capacity Limit
Envisioned as one of the most promising technologies, holographic
multiple-input multiple-output (H-MIMO) recently attracts notable research
interests for its great potential in expanding wireless possibilities and
achieving fundamental wireless limits. Empowered by the nearly continuous,
large and energy-efficient surfaces with powerful electromagnetic (EM) wave
control capabilities, H-MIMO opens up the opportunity for signal processing in
a more fundamental EM-domain, paving the way for realizing holographic imaging
level communications in supporting the extremely high spectral efficiency and
energy efficiency in future networks. In this article, we try to implement a
generalized EM-domain near-field channel modeling and study its capacity limit
of point-to-point H-MIMO systems that equips arbitrarily placed surfaces in a
line-of-sight (LoS) environment. Two effective and computational-efficient
channel models are established from their integral counterpart, where one is
with a sophisticated formula but showcases more accurate, and another is
concise with a slight precision sacrifice. Furthermore, we unveil the capacity
limit using our channel model, and derive a tight upper bound based upon an
elaborately built analytical framework. Our result reveals that the capacity
limit grows logarithmically with the product of transmit element area, receive
element area, and the combined effects of , ,
and over all transmit and receive antenna elements, where
indicates the distance between each transmit and receive elements.
Numerical evaluations validate the effectiveness of our channel models, and
showcase the slight disparity between the upper bound and the exact capacity,
which is beneficial for predicting practical system performance.Comment: 30 pages, 8 figure
Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions
Future wireless systems are envisioned to create an endogenously
holography-capable, intelligent, and programmable radio propagation
environment, that will offer unprecedented capabilities for high spectral and
energy efficiency, low latency, and massive connectivity. A potential and
promising technology for supporting the expected extreme requirements of the
sixth-generation (6G) communication systems is the concept of the holographic
multiple-input multiple-output (HMIMO), which will actualize holographic radios
with reasonable power consumption and fabrication cost. The HMIMO is
facilitated by ultra-thin, extremely large, and nearly continuous surfaces that
incorporate reconfigurable and sub-wavelength-spaced antennas and/or
metamaterials. Such surfaces comprising dense electromagnetic (EM) excited
elements are capable of recording and manipulating impinging fields with utmost
flexibility and precision, as well as with reduced cost and power consumption,
thereby shaping arbitrary-intended EM waves with high energy efficiency. The
powerful EM processing capability of HMIMO opens up the possibility of wireless
communications of holographic imaging level, paving the way for signal
processing techniques realized in the EM-domain, possibly in conjunction with
their digital-domain counterparts. However, in spite of the significant
potential, the studies on HMIMO communications are still at an initial stage,
its fundamental limits remain to be unveiled, and a certain number of critical
technical challenges need to be addressed. In this survey, we present a
comprehensive overview of the latest advances in the HMIMO communications
paradigm, with a special focus on their physical aspects, their theoretical
foundations, as well as the enabling technologies for HMIMO systems. We also
compare the HMIMO with existing multi-antenna technologies, especially the
massive MIMO, present various...Comment: double column, 58 page
Hybrid Beamforming Design for Self-Interference Cancellation in Full-Duplex Millimeter-Wave MIMO Systems with Dynamic Subarrays
Full-duplex (FD) millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication is a promising solution for the extremely high-throughput requirements in future cellular systems. The hybrid beamforming structure is preferable for its low hardware complexity and low power consumption with acceptable performance. In this paper, we introduce the hardware efficient dynamic subarrays to the FD mmWave MIMO systems and propose an effective hybrid beamforming design to cancel the self-interference (SI) in the considered system. First, assuming no SI, we obtain the optimal fully digital beamformers and combiners via the singular value decomposition of the uplink and downlink channels and the water-filling power allocation. Then, based on the obtained fully digital solutions, we get the dynamic analog solutions and digital solutions using the KuhnâMunkres algorithm-aided dynamic hybrid beamforming design. Finally, we resort to the null space projection method to cancel the SI by projecting the obtained digital beamformer at the base station onto the null space of the equivalent SI channel. We further analyze the computational complexity of the proposed method. Numerical results demonstrate the superiority of the FD mmWave MIMO systems with the dynamic subarrays using the proposed method compared to the systems with the fixed subarrays and the half-duplex mmWave communications. When the number of RF chains is 6 and the signal-to-noise ratio is 10 dB, the proposed design outperforms the FD mmWave MIMO systems with fixed subarrays and the half-duplex mmWave communications, respectively, by 22.4% and 47.9% in spectral efficiency and 19.9% and 101% in energy efficiency
Compressive Subspace Learning Based Wideband Spectrum Sensing for Multiantenna Cognitive Radio
Recently, sub-Nyquist sampling (SNS) based wideband spectrum sensing has emerged as a promising approach for cognitive radios. However, most of existing SNS-based approaches cannot effectively deal with the wireless channel fading due to the lack of space diversity exploitation, which would lead to poor sensing performance. To address the problem, we propose a multi-antenna system, referred to as the multiantenna generalized modulated converter (MAGMC), to realize the SNS, where spatially correlated multiple-input multiple-output (MIMO) channel is considered. Based on the multiantenna system, two compressive subspace learning (CSL) approaches (mCSL and vCSL) are proposed for signal subspace learning, where wideband sectrum sensing is realized based on the signal subspace. Both proposedCSLapproaches exploit space diversity, where the mCSL utilizes an antenna averaging temporal decomposition, and the vCSL (which is formulated based on a vectorization of sample matrix in the mCSL) uses a spatial-temporal joint decomposition. We further establish analytical relationships between eigenvalues of statistical covariance matrices in statistical sense in both multiantenna and single antenna scenarios. Space diversity and superiority over the single antenna scenario for both proposed CSL approaches are analyzed based on the derived analytical relationships. Moreover, the mCSL and vCSL based wideband spectrum sensing algorithms are proposed based on the system model of MAGMC and their computational complexities are given. The proposed CSL based wideband spectrum sensing algorithms can effectively dealwith the wireless channel fading and simulations show the improvement on performance of wideband spectrum sensing over related works
Property Investigation on the Additive White Gaussian Noise After Sub-Nyquist Sampling
The sub-Nyquist sampling (SNS) has emerged as an appealing technique for wideband signal sampling and has found its applications in many areas, such as, cognitive radios, radar and medical imaging, etc.. However, existing SNS based approaches generally assume that the output noise of SNS (termed as SNS noise) is generated as the additive white Gaussian noise without considering the SNS effect. To give more insights on the noise after SNS, we propose a generalized modulated converter to represent existing prevalent SNS systems and give an analysis on statistics of the SNS noise in terms of the proposed SNS system. The noise folding factor and the uncorrelated and white keeping properties are derived and concluded from the derived statistics, in which the former is used to show the noise enhancement by SNS and the latter describes the SNS noise uncorrelation and equal power intensity in different frequencies, respectively. In the final, simulation results validate the derived results and conclusions
Dynamic Ti3+ and In3+ dual active sites on In2TiO5 to enhance visible-light-driven gas-phase photocatalytic CO2 reduction
Amorphous materials offer novel and cooperative active sites that challenge the limits of heterogeneous crystalline catalysts. This work represents an initial development of a feasible amorphous photocatalyst for CO2 photoreduction. We optimise the bandgap and crystal structure of amorphous In2TiO5 to facilitate the conversion of CO2 to CH4. The XAFS analysis identifies Ti3+ as the active site. The reaction between H2O and In3+ produces protons that lower the oxidation state of In3+ to In2+. Moreover, adding 2D nanolayers of MoSe2 to In2TiO5 increases CH4 production from 4.14 to 6.15 ”mol/g. We report the effect of multiphoton flux and find that it leads to a 1.28-fold increase in CH4 production. The combined in situ DRIFTS and DFT analyses elucidate underlying chemical pathways in photocatalytic CO2 reduction. © 2023 Elsevier B.V.FALS