On the Performance of Downlink MIMO-ISAC

This letter analyzes the performance of sensing and communications (S\&C) achieved by a multiple-input multiple-output downlink integrated S\&C (ISAC) system. Three typical ISAC scenarios are studied, including the sensing-centric design, communications-centric design, and Pareto optimal design. For each scenario, diversity orders and high signal-to-noise ratio slopes of the sensing rate and communication rate are derived to gain further insights. It is found that ISAC can provide more degrees of freedom and a broader rate region than existing frequency-division S\&C (FDSAC) techniques.Comment: 5 page

Learning Automata Based Q-Learning for Content Placement in Cooperative Caching

Author's accepted manuscript.© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.acceptedVersio

Catalytic Removal of Ozone by Pd/ACFs and Optimal Design of Ozone Converter for Air Purification in Aircraft Cabin

Ozone in aircraft cabin can bring obvious adverse impact on indoor air quality and occupant health. The objective of this study is to experimentally explore the ozone removal performance of flat-type catalyst film by loading nanometer palladium on the activated carbon fibers (Pd/ACFs), and optimize the configuration of ozone converter to make it meet the design requirements. A one-through ozone removal unit with three different Pd/ACFs space was used to test the ozone removal performance and the flow resistance characteristic under various temperature and flow velocity. The results show that the ozone removal rate of the ozone removal unit with the Pd/ACFs space of 1.5 mm can reach 99% and the maximum pressure drop is only 1.9 kPa at the reaction temperature of 200℃. The relationship between pressure drop and flow velocity in the ozone removal unit has a good fit to the Darcy-Forchheimer model. An ozone converter with flat-type reactor was designed and processed based on the one-through ozone removal experiment, its ozone removal rate and maximum pressure drop were 97% and 7.51 kPa, separately, with the condition of 150℃ and 10.63 m/s. It can meet the design requirements of ozone converter for air purification and develop a healthier aircraft cabin environment

Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?

With the aim of integrating over-the-air federated learning (AirFL) and non-orthogonal multiple access (NOMA) into an on-demand universal framework, this paper proposes a novel reconfigurable intelligent surface (RIS)-aided hybrid network by leveraging the RIS to flexibly adjust the signal processing order of heterogeneous data. The objective of this work is to maximize the achievable hybrid rate by jointly optimizing the transmit power, controlling the receive scalar, and designing the phase shifts. Since the concurrent transmissions of all computation and communication signals are aided by the discrete phase shifts at the RIS, the considered problem (P0) is a challenging mixed integer programming problem. To tackle this intractable issue, we decompose the original problem (P0) into a non-convex problem (P1) and a combinatorial problem (P2), which are characterized by the continuous and discrete variables, respectively. For the transceiver design problem (P1), the power allocation subproblem is first solved by invoking the difference-of-convex programming, and then the receive control subproblem is addressed by using the successive convex approximation, where the closed-form expressions of simplified cases are derived to obtain deep insights. For the reflection design problem (P2), the relaxation-then-quantization method is adopted to find a suboptimal solution for striking a trade-off between complexity and performance. Afterwards, an alternating optimization algorithm is developed to solve the non-linear and non-convex problem (P0) iteratively. Finally, simulation results reveal that 1) the proposed RIS-aided hybrid network can support the on-demand communication and computation efficiently, 2) the performance gains can be improved by properly selecting the location of the RIS, and 3) the designed algorithms are also applicable to conventional networks with only AirFL or NOMA users

STAR-RIS Enabled Heterogeneous Networks: Ubiquitous NOMA Communication and Pervasive Federated Learning

This paper integrates non-orthogonal multiple access (NOMA) and over-the-air federated learning (AirFL) into a unified framework using a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). The STAR-RIS plays an important role in adjusting the decoding order of hybrid users for efficient interference mitigation and omni-directional coverage extension. To capture the impact of non-ideal wireless channels on AirFL, a closed-form expression for the optimality gap (a.k.a. convergence upper bound) between the actual loss and the optimal loss is derived. This analysis reveals that the learning performance is significantly affected by active and passive beamforming schemes as well as wireless noise. Furthermore, when the learning rate diminishes as the training proceeds, the optimality gap is explicitly characterized to converge with a linear rate. To accelerate convergence while satisfying QoS requirements, a mixed-integer non-linear programming (MINLP) problem is formulated by jointly designing the transmit power at users and the configuration mode of STAR-RIS. Next, a trust region-based successive convex approximation method and a penalty-based semidefinite relaxation approach is proposed to handle the decoupled non-convex subproblems iteratively. An alternating optimization algorithm is then developed to find a suboptimal solution for the original MINLP problem. Extensive simulation results show that i) the proposed framework can efficiently support NOMA and AirFL users via concurrent uplink communications, ii) our algorithms can achieve a faster convergence rate on the IID and non-IID settings as compared to baselines, and iii) both the spectrum efficiency and learning performance can be significantly improved with the aid of the well-tuned STAR-RIS.Comment: 16 pages, 8 figure