Integrated sensing and communication (ISAC) emerges as a new design paradigm that combines both sensing and communication systems to jointly utilize their resources and to pursue mutual benefits for future B5G and 6G networks. In ISAC, the hardware and spectrum co-sharing leads to a fundamental tradeoff between sensing and communication performance, which is not well understood except for very simple cases with the same sensing and channel states, and perfect channel state information at the receiver (CSIR). In this paper, a more general point-to-point ISAC model is proposed to account for the scenarios that the sensing state is different from but correlated with the channel state, and the CSIR is not necessarily perfect. For the model considered, the optimal tradeoff is characterized by a capacity-distortion function that quantifies the best communication rate for a given sensing distortion constraint requirement. An iterative algorithm is proposed to compute such tradeoff, and a few non-trivial examples are constructed to demonstrate the benefits of ISAC as compared to the separation-based approach.
相關內容
Integration：Integration, the VLSI Journal。
Explanation：集成，VLSI雜志。
Publisher：Elsevier。
SIT：
Practical Hybrid Beamforming for Millimeter Wave Massive MIMO Full Duplex with Limited Dynamic Range
In this paper, we present a novel hybrid beamforming (HYBF) design to maximize the weighted sum-rate (WSR) in a single-cell millimeter-wave (mmWave) massive multiple-input-multiple-output (MIMO) full duplex (FD) system. Compared to the traditional HYBF designs, we consider the joint sum-power and the practical per-antenna power constraints. The multi-antenna users and the hybrid FD base station (BS) are assumed to be suffering from the limited dynamic range (LDR) noise due to non-ideal hardware. The traditional LDR noise model is first extended to the mmWave and an impairment-aware HYBF approach is adopted. A novel interference, self-interference (SI) and LDR aware optimal power allocation scheme for the multi-antenna uplink (UL) users and the hybrid FD BS is also presented. The analog processing stage is assumed to be quantized, and both the unit-modulus and the unconstrained cases are studied. The maximum achievable gain of a multi-user mmWave FD system over a fully digital half duplex (HD) system with different levels of the LDR noise variance and different numbers of the radio-frequency (RF) chains is investigated. Simulation results show that the proposed HYBF design outperforms the fully digital HD system with only a few RF chains at any LDR noise level. The advantage of having amplitude control at the analog stage is also examined and additional gain is evident when the number of RF chains at the FD BS is small.
In this paper, we investigate the performance of an intelligent omni-surface (IOS) assisted downlink non-orthogonal multiple access (NOMA) network with phase quantization errors and channel estimation errors, where the channels related to the IOS are spatially correlated. First, upper bounds on the average achievable rates of the two users are derived. Then, channel hardening is shown to occur in the proposed system, based on which we derive approximations of the average achievable rates of the two users. The analytical results illustrate that the proposed upper bound and approximation on the average achievable rate of the strong user are asymptotically equivalent in the number of elements. Furthermore, it is proved that the average achievable rates with correlated and uncorrelated channels are asymptotically equivalent for a large number of elements. Simulation results corroborate the theoretical analysis and show that the channel hardening effect appears even for a few elements. The impact of channel correlation on the system performance in terms of average achievable rates is negligible for a large number of elements.
Wireless signals are commonly used for communications. Emerging applications are giving new functions to wireless signals, in which wireless sensing is the most attractive one. Channel state information (CSI) is not only the parameter for channel equalization in communications but also the indicator for wireless sensing. However, due to the broadcast nature of wireless signals, eavesdroppers can easily capture legitimate user signals and violate user privacy by measuring CSI. Moreover, the advancement of hardware simplifies illegal eavesdropping since smart devices can track over-the-air signals through walls. Therefore, this work considers a waveform-defined privacy (WDP) solution that can hide CSI phase information and therefore protect user privacy. Besides, the proposed waveform solution achieves better performance due to the use of a unique modulation mechanism. Additionally, by tuning a waveform parameter, the waveform can also enhance communication security.
In this paper, we investigate the impact of side information (SI) on the performance of physical layer security (PLS) under correlated Rayleigh fading channels. By considering non-causally known SI at the transmitter and exploiting the copula technique to describe the fading correlation, we derived closed-from expressions for the average secrecy capacity (ASC) and secrecy outage probability (SOP) under positive/negative dependence conditions. We indicate that considering such knowledge at the transmitter is beneficial for system performance and ensures reliable communication with higher rates, as it improves the SOP and brings higher values of the ASC.
We show that the one-dimensional (1D) two-fluid model (TFM) for stratified flow in channels and pipes (in its incompressible, isothermal form) satisfies an energy conservation equation, which arises naturally from the mass and momentum conservation equations that constitute the model. This result extends upon earlier work on the shallow water equations (SWE), with the important difference that we include non-conservative pressure terms in the analysis, and that we propose a formulation that holds for ducts with an arbitrary cross-sectional shape, with the 2D channel and circular pipe geometries as special cases. The second novel result of this work is the formulation of a finite volume scheme for the TFM that satisfies a discrete form of the continuous energy equation. This discretization is derived in a manner that runs parallel to the continuous analysis. Due to the non-conservative pressure terms it is essential to employ a staggered grid, which requires careful consideration in defining the discrete energy and energy fluxes, and the relations between them and the discrete model. Numerical simulations confirm that the discrete energy is conserved.
We address the detection of material defects, which are inside a layered material structure using compressive sensing based multiple-input and multiple-output (MIMO) wireless radar. Here, the strong clutter due to the reflection of the layered structure's surface often makes the detection of the defects challenging. Thus, sophisticated signal separation methods are required for improved defect detection. In many scenarios, the number of defects that we are interested in is limited and the signaling response of the layered structure can be modeled as a low-rank structure. Therefore, we propose joint rank and sparsity minimization for defect detection. In particular, we propose a non-convex approach based on the iteratively reweighted nuclear and $\ell_1-$norm (a double-reweighted approach) to obtain a higher accuracy compared to the conventional nuclear norm and $\ell_1-$norm minimization. To this end, an iterative algorithm is designed to estimate the low-rank and sparse contributions. Further, we propose deep learning to learn the parameters of the algorithm (i.e., algorithm unfolding) to improve the accuracy and the speed of convergence of the algorithm. Our numerical results show that the proposed approach outperforms the conventional approaches in terms of mean square errors of the recovered low-rank and sparse components and the speed of convergence.
Molecular communication (MC) can enable the transfer of information between nanomachines using molecules as the information carrier. In MC systems, multiple receiver nanomachines often co-exist in the same communication channel to serve common or different purposes. However, the analytical channel model for a system with multiple fully absorbing receivers (FARs) does not exist in the literature, which is significantly different from the single FAR system due to the mutual influence of FARs. The analytical channel model is essential in analyzing systems with multiple FARs, including MIMO, SIMO, and cognitive molecular communication systems. In this work, we derive an approximate analytical expression for the hitting probability of a molecule emitted from a point source on each FAR on a diffusion-based MC system with three or more FARs. Using these expressions, we derive the channel model for a SIMO system with a single transmitter and multiple FARs arranged in a uniform circular array (UCA). We then analyze the communication performance of this SIMO system under different cooperative receiver schemes and develop several interesting insights.
Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an aggregated channel estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability.
In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training with fully utilizing their computational resources. It is well acknowledged that step asynchronism leads to objective inconsistency under non-i.i.d. data, which degrades the model accuracy. To address this issue, we propose a new algorithm \texttt{FedaGrac}, which calibrates the local direction to a predictive global orientation. Taking the advantage of estimated orientation, we guarantee that the aggregated model does not excessively deviate from the expected orientation while fully utilizing the local updates of faster nodes. We theoretically prove that \texttt{FedaGrac} holds an improved order of convergence rate than the state-of-the-art approaches and eliminates the negative effect of step asynchronism. Empirical results show that our algorithm accelerates the training and enhances the final accuracy.
A non-orthogonal multiple access (NOMA) inspired integrated sensing and communication (ISAC) system is investigated. A dual-functional base station (BS) serves multiple communication users while sensing multiple targets, by transmitting the non-orthogonal superposition of the communication and sensing signals. A NOMA inspired interference cancellation scheme is proposed, where part of the dedicated sensing signal is treated as the virtual communication signals to be mitigated at each communication user via successive interference cancellation (SIC). Based on this framework, the transmitted communication and sensing signals are jointly optimized to match the desired sensing beampattern, while satisfying the minimum rate requirement and the SIC condition at the communication users. Then, the formulated non-convex optimization problem is solved by invoking the successive convex approximation (SCA) to obtain a near-optimal solution. The numerical results show the proposed NOMA-inspired ISAC system can achieve better performance than the conventional ISAC system and comparable performance to the ideal ISAC system where all sensing interference is assumed to be removed unconditionally.
小貼士
登錄享
注冊地址： 北京市海淀區羊坊店路18號2幢3層301-191