Statistical model for MIMO propagation channel in cavities and random media

Gradoni, Gabriele; Richter, Martin; Phang, Sendy; Fedeli, Sirio Belga; Kuhl, Ulrich; Legrand, Olivier; Ishimaru, Akira

doi:10.23919/ursigass49373.2020.9232187

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Experiments confirm the monotonicity of its mean and variance as function of absorption [25]. The appearance of two curves in Figs.17,18 is due to the selective excitement of the transmit antennas while measuring the channel coefficient at two receiver antennas.…”

Section: G Distribution Of the Channel Capacitymentioning

confidence: 55%

Statistical Characterization of Wireless MIMO Channels in Mode-Stirred Enclosures

Lodro,

Greedy,

Fedeli

et al. 2021

Preprint

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We present the statistical characterization of a 2x2 Multiple-Input Multiple-Output wireless link operated in a modestirred enclosure, with channel state information available only at the receiver (agnostic transmitter). Our wireless channel measurements are conducted in absence of line of sight and varying the inter-element spacing between the two antenna elements in both the transmit and receive array. The mode-stirred cavity is operated: i) at a low number of stirrer positions to create statistical inhomogeneity; ii) at two different loading conditions, empty and with absorbers, in order to mimic a wide range of realistic equipment level enclosures. Our results show that two parallel channels are obtained within the confined space at both the operating conditions. The statistical characterization of the wireless channel is presented in terms of coherence bandwidth, path loss, delay spread and Rician factor, and wideband channel capacity. It is found that the severe multipath fading supported by a highly reflecting environment creates unbalance between the two Multiple-Input Multiple-Output channels, even in presence of substantial losses. Furthermore, the channel capacity has a multi-modal distribution whose average and variance scale monotonically with the number of absorbers. Results are of interest in IoT devices, including wireless chip-to-chip and device-to-device communications, operating in highly reflective environments.

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Section: G Distribution Of the Channel Capacitymentioning

confidence: 55%

Statistical Characterization of Wireless MIMO Channels in Mode-Stirred Enclosures

Lodro,

Greedy,

Fedeli

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Also, according to the first-principle model in [17], the term Z LOS in (5) captures the single (short-orbit) LOS channels between RIS unit cells and transmit/receive array elements in the far-field approximation. It is worth remarking that [18] (6) with Z f s (n, n) free-space (f s) active impedance of the n-th antenna element.…”

Section: A Mimo Communication Model Overviewmentioning

confidence: 99%

Quantum Optimisation of Reconfigurable Surfaces in Complex Propagation Environments

Colella,

Bastianelli,

Khalily

et al. 2024

2024 18th European Conference on Antennas and Propagation (EuCAP)

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The design and analysis of reconfigurable metasurfaces operating within rich multi-path propagation fading is of crucial importance for the development of real-life programmable electromagnetic environments. We incorporate the effect of multipath fading in an impedance-based model of wireless communication links assisted by reconfigurable surfaces. Previous work has shown that impedance-based channel models under rich multi-path propagation have an isomorphism with Sherrington-Kirkpatrick (SK) Hamiltonians. We focus on received power minimisation, which is equivalent to the hard-to-solve task task of finding the ground state of the SK Hamiltonian. It has been recently discovered that the Quantum Approximate Optimisation Algorithm (QAOA) predicts the ground state of SK Hamiltonians accurately. However, the landscape parameters of QAOA are dependent on the specific realisation of the random SK Hamiltonian, which hinders the full usage of quantum hardware to optimise reconfigurable surfaces dynamically. We show by Montecarlo simulations that a concentration property cures this impediment thus making QAOA an excellent candidate for surface optimisation under fast multi-path fading.

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