pwc-archive/papers-with-abstracts huggingface dataset:
Min-Max Framework for Majorization-Minimization Algorithms in Signal Processing Applications: An Overview
Authors: Astha Saini, Petre Stoica, Prabhu Babu, Aakash Arora
Date: 2024-11-12 00:00:00

This monograph presents a theoretical background and a broad introduction to the Min-Max Framework for Majorization-Minimization (MM4MM), an algorithmic methodology for solving minimization problems by formulating them as min-max problems and then employing majorization-minimization. The monograph lays out the mathematical basis of the approach used to reformulate a minimization problem as a min-max problem. With the prerequisites covered, including multiple illustrations of the formulations for convex and non-convex functions, this work serves as a guide for developing MM4MM-based algorithms for solving non-convex optimization problems in various areas of signal processing. As special cases, we discuss using the majorization-minimization technique to solve min-max problems encountered in signal processing applications and min-max problems formulated using the Lagrangian. Lastly, we present detailed examples of using MM4MM in ten signal processing applications such as phase retrieval, source localization, independent vector analysis, beamforming and optimal sensor placement in wireless sensor networks. The devised MM4MM algorithms are free of hyper-parameters and enjoy the advantages inherited from the use of the majorization-minimization technique such as monotonicity.
Reference Signal-Based Waveform Design for Integrated Sensing and Communications System
Authors: Ming Lyu, Hao Chen, Dan Wang, Guangyin Feng, Chen Qiu, Xiaodong Xu
Date: 2024-11-12 00:00:00
Tasks: ISAC

Integrated sensing and communications (ISAC) as one of the key technologies is capable of supporting high-speed communication and high-precision sensing for the upcoming 6G. This paper studies a waveform strategy by designing the orthogonal frequency division multiplexing (OFDM)-based reference signal (RS) for sensing and communication in ISAC system. We derive the closed-form expressions of Cram\'er-Rao Bound (CRB) for the distance and velocity estimations, and obtain the communication rate under the mean square error of channel estimation. Then, a weighted sum CRB minimization problem on the distance and velocity estimations is formulated by considering communication rate requirement and RS intervals constraints, which is a mixed-integer problem due to the discrete RS interval values. To solve this problem, some numerical methods are typically adopted to obtain the optimal solutions, whose computational complexity grow exponentially with the number of symbols and subcarriers of OFDM. Therefore, we propose a relaxation and approximation method to transform the original discrete problem into a continuous convex one and obtain the sub-optimal solutions. Finally, our proposed scheme is compared with the exhaustive search method in numerical simulations, which show slight gap between the obtained sub-optimal and optimal solutions, and this gap further decreases with large weight factor.
Double Media-Based Modulation Scheme for High-Rate Wireless Communication Systems
Authors: Burak Ahmet Ozden, Erdogan Aydin, Fatih Cogen
Date: 2024-11-11 00:00:00

Current wireless communication technologies are insufficient in the face of ever-increasing demands. Therefore, novel and high-performance communication systems are needed. In this paper, a novel high data rate and high-performance index modulation scheme called double media-based modulation (DMBM) is proposed. The DMBM system doubles the number of mirror activation patterns (MAPs) and the number of transmitted symbols compared to the traditional MBM system during the same symbol period. In this way, the spectral efficiency of the DMBM is doubled and the error performance improves as the number of bits carried in the indices increases. Performance analysis of the DMBM scheme is evaluated for $M$-ary quadrature amplitude modulation ($M$-QAM) on Rayleigh fading channels. The error performance of the proposed DMBM system is compared with spatial modulation (SM), quadrature SM (QSM), MBM, and double SM (DSM) techniques. Also, the throughput, complexity, energy efficiency, spectral efficiency, and capacity analyses for the proposed DMBM system and SM, QSM, MBM, and DSM systems are presented. All analysis results show that the proposed DMBM system is superior to the compared systems.
LOS/NLOS Estimators for mmWave Cellular Systems With Blockages
Authors: Tomàs Ortega, Antonio Pascual-Iserte, Olga Muñoz
Date: 2024-11-11 00:00:00
Tasks: Blocking

Designers of millimeter wave (mmWave) cellular systems need to evaluate line-of-sight (LOS) maps to provide good service to users in urban scenarios. In this letter, we derive estimators to obtain LOS maps in scenarios with potential blocking elements. Applying previous stochastic geometry results, we formulate the optimal Bayesian estimator of the LOS map using a limited number of actual measurements at different locations. The computational cost of the optimal estimator is derived and is proven to be exponential in the number of available data points. An approximation is discussed, which brings the computational complexity from exponential to quasi-linear and allows the implementation of a practical estimator. Finally, we compare numerically the optimal estimator and the approximation with other estimators from the literature and also with an original heuristic estimator with good performance and low computational cost. For the comparison, both synthetic layouts and a real layout of Chicago have been used.
Ultra-Wideband Communications: A New Spectrum Survey and Challenges Ahead
Authors: Brian Nelson, Hussein Moradi, Behrouz Farhang-Boroujeny
Date: 2024-11-11 00:00:00
Tasks: Survey

The idea of ultra-wideband (UWB) communications for short ranges (up to a few tens of meters) has been around for nearly three decades. However, despite significant efforts by the industry, UWB deployment has not yet reached its predicted potential. This article, thus, seeks to rectify this situation by providing a practical examination of UWB interference conditions. Through a spectrum survey of today's wireless environments, we quantify the level of interference that UWB devices may face and explore the signal processing steps that must be taken to materialize the full potential of UWB communications.
DoF Analysis and Beamforming Design for Active IRS-aided Multi-user MIMO Wireless Communication in Rank-deficient Channels
Authors: Feng Shu, Jinbing Jiang, Xuehui Wang, Ke Yang, Chong Shen, Qi Zhang, Dongming Wang, Jiangzhou Wang
Date: 2024-11-11 00:00:00

Due to its ability of significantly improving data rate, intelligent reflecting surface (IRS) will be a potential crucial technique for the future generation wireless networks like 6G. In this paper, we will focus on the analysis of degree of freedom (DoF) in IRS-aided multi-user MIMO network. Firstly, the DoF upper bound of IRS-aided single-user MIMO network, i.e., the achievable maximum DoF of such a system, is derived, and the corresponding results are extended to the case of IRS-aided multiuser MIMO by using the matrix rank inequalities. In particular, in serious rank-deficient, also called low-rank, channels like line-of-sight (LoS), the network DoF may doubles over no-IRS with the help of IRS. To verify the rate performance gain from augmented DoF, three closed-form beamforming methods, null-space projection plus maximize transmit power and maximize receive power (NSP-MTP-MRP), Schmidt orthogonalization plus minimum mean square error (SO-MMSE) and two-layer leakage plus MMSE (TLL-MMSE) are proposed to achieve the maximum DoF. Simulation results shows that IRS does make a dramatic rate enhancement. For example, in a serious deficient channel, the sum-rate of the proposed TLL-MMSE aided by IRS is about twice that of no IRS. This means that IRS may achieve a significant DoF improvement in such a channel.
Sensing Capacity for Integrated Sensing and Communication Systems in Low-Altitude Economy
Authors: Jiahua Wan, Hong Ren, Cunhua Pan, Zhenkun Zhang, Songtao Gao, Yiming Yu, Chengzhong Wang
Date: 2024-11-11 00:00:00
Tasks: Integrated sensing and communication, ISAC, Scheduling

The burgeoning significance of the low-altitude economy (LAE) has garnered considerable interest, largely fuelled by the widespread deployment of unmanned aerial vehicles (UAVs). To tackle the challenges associated with the detection of unauthorized UAVs and the efficient scheduling of authorized UAVs, this letter introduces a novel performance metric, termed sensing capacity, for integrated sensing and communication (ISAC) systems. This metric, which quantifies the capability of a base station (BS) to detect multiple UAVs simultaneously, leverages signal-to-noise ratio (SNR) and probability of detection (PD) as key intermediate variables. Through mathematical derivations, we can derive a closed-form solution for the maximum number of UAVs that can be detected by the BS while adhering to a specific SNR constraint. Furthermore, an approximate solution based on PD constraints is proposed to facilitate the efficient determination of the threshold for the maximum number of detectable UAVs. The accuracy of this analytical approach is verified through extensive simulation results.
Multi-Connectivity Solutions for Rural Areas: Integrating Terrestrial 5G and Satellite Networks to Support Innovative IoT Use Cases
Authors: Alejandro Ramírez-Arroyo, Melisa López, Ignacio Rodríguez, Sebastian Bro Damsgaard, Preben Mogensen
Date: 2024-11-11 00:00:00

5G cellular networks are now a reality and promise to improve key performance indicators (KPIs), such as Gbps data rates and latencies in the order of milliseconds. While some of these KPIs are achievable in urban scenarios, rural areas often face challenging connectivity conditions due to the lack of terrestrial network (TN) infrastructure. To solve this problem, non-terrestrial networks (NTNs) such as satellite-based solutions, have been introduced to provide coverage in remote regions. Therefore, a multi-connectivity approach can be integrated to simultaneously serve an end-user by merging satellite and cellular links in a joint approach. This study explores, using experimental data, the benefits of both TN-TN and TN-NTN multi-connectivity in rural environments. The results obtained demonstrate that a traditional single-connectivity approach may not be sufficient to provide service to rural environments due to the KPIs requirements given several use cases within these rural areas. The multi-connectivity strategy, which jointly integrates 5G and satellite networks, meets the network availability requirements for latency, downlink throughput, and uplink throughput KPIs at least 98%, 99%, and 95% of the time, respectively, for several use cases, such as precision agriculture, livestock monitoring, and forest management. These include applications like microclimate monitoring, remote operational support, early pest detection, and real-time tracking of livestock transport.
An Electrocardiogram Monitoring Device Based on STM32
Authors: Wenqi Guan
Date: 2024-11-11 00:00:00

Cardiovascular diseases remain the leading cause of morbidity and mortality, particularly in aging populations, with rising rates of heart-related incidents in middle-aged and even younger individuals. Currently available electrocardiogram (ECG) monitoring technologies, such as bedside monitors are bulky and cumbersome, limiting their potential accessibility for continuous, real-time monitoring. Therefore, we propose a portable digital ECG monitoring system that can accurately measure heart rate, analyze the ECG in real-time, and wirelessly send data to the cloud platform. The device comprises a custom-designed circuit to capture ECG signals, with analog-to-digital conversion and heart rate measurement performed by an STM32F429 microcontroller. In addition, real-time monitoring is achieved through the L610-4G module, which transmits data to Tencent Cloud, enabling users to access their ECG data remotely while being notified by instant alerts for abnormal heart rates. Moreover, healthcare professionals can view historic ECG data for further clinical analysis of patient progression and make evidence-based decisions. The proposed system features portability and accuracy, enabling the user to access extended ECG data easily. It provides the ability to minimize redundant clinical assessments, thus offering considerable advantages to patients and healthcare practitioners.
DeepCRF: Deep Learning-Enhanced CSI-Based RF Fingerprinting for Channel-Resilient WiFi Device Identification
Authors: Ruiqi Kong, He Chen
Date: 2024-11-11 00:00:00
Tasks: Contrastive Learning, Data Augmentation

This paper presents DeepCRF, a new framework that harnesses deep learning to extract subtle micro-signals from channel state information (CSI) measurements, enabling robust and resilient radio-frequency fingerprinting (RFF) of commercial-off-the-shelf (COTS) WiFi devices across diverse channel conditions. Building on our previous research, which demonstrated that micro-signals in CSI, termed micro-CSI, most likely originate from RF circuitry imperfections and can serve as unique RF fingerprints, we develop a new approach to overcome the limitations of our prior signal space-based method. While the signal space-based method is effective in strong line-of-sight (LoS) conditions, we show that it struggles with the complexities of non-line-of-sight (NLoS) scenarios, compromising the robustness of CSI-based RFF. To address this challenge, DeepCRF incorporates a carefully trained convolutional neural network (CNN) with model-inspired data augmentation, supervised contrastive learning, and decision fusion techniques, enhancing its generalization capabilities across unseen channel conditions and resilience against noise. Our evaluations demonstrate that DeepCRF significantly improves device identification accuracy across diverse channels, outperforming both the signal space-based baseline and state-of-the-art neural network-based benchmarks. Notably, it achieves an average identification accuracy of 99.53% among 19 COTS WiFi network interface cards in real-world unseen scenarios using 4 CSI measurements per identification procedure.
Annotation and synchronization of smartphone inertial measurement unit and motion capture data collected in a laboratory setting to study gait and balance
Authors: Dimitar Stanev, Rafał Klimas, Marta Płonka, Natan Napiórkowski, Lorenza Angelini, Tjitske A. Boonstra, Gabriela Gonzalez Chan, Jonathan Marsden, Mike D. Rinderknecht, Mattia Zanon
Date: 2024-11-11 00:00:00

Validating smartphone sensor-based tests to study gait and balance against reference measurement systems in a laboratory setting poses several technical challenges related to data quality and data processing. One challenge is to guarantee the correct annotation of the data, which is required to ensure that only data collected during the same test execution are compared across measurement systems in subsequent analyses. A second challenge is to accurately synchronize the data across the different systems. Here, we propose innovative solutions for both challenges and illustrate their use in the example of comparing smartphone sensor data collected with the Floodlight technology with data collected with a motion capture system. These solutions form important tools for guaranteeing the data quality and data integrity required for the validation of gait and balance characteristics measured by digital health technology tools such as the Floodlight technology.
Multi-Static Cell-Free Massive MIMO ISAC: Performance Analysis and Power Allocation
Authors: Nhan Thanh Nguyen, Tianyu Fang, Hien Quoc Ngo, Markku Juntti
Date: 2024-11-11 00:00:00
Tasks: ISAC

In this work, we consider a cell-free massive multiple-input multiple-output (MIMO) integarted sensing and communications (ISAC) system with maximum-ratio transmission schemes combined with multistatic radar-type sensing. Our focus lies on deriving closed-form expressions for the achievable communications rate and the Cram\'er-Rao lower bound (CRLB), which serve as performance metrics for communications and sensing operations, respectively. The expressions enable us to investigate important operational characteristics of multistatic cell-free massive MIMO-ISAC, including the mutual effects of communications and sensing as well as the advantages stemming from using numerous distributed antenna arrays for each functionality. Furthermore, we optimize the power allocation among the access points to maximize the communications rate while guaranteeing the CRLB constraints and total transmit power budget. Extensive numerical results are presented to validate our theoretical findings and demonstrate the efficiency of the proposed power allocation approach.
Movable Antenna-Aided Federated Learning with Over-the-Air Aggregation: Joint Optimization of Positioning, Beamforming, and User Selection
Authors: Yang Zhao, Yue Xiu, Minrui Xu, Ning Wei
Date: 2024-11-11 00:00:00
Tasks: Federated Learning, Stochastic Optimization

Federated learning (FL) in wireless computing effectively utilizes communication bandwidth, yet it is vulnerable to errors during the analog aggregation process. While removing users with unfavorable channel conditions can mitigate these errors, it also reduces the available local training data for FL, which in turn hinders the convergence rate of the training process. To tackle this issue, we propose the use of movable antenna (MA) techniques to enhance the degrees of freedom within the channel space, ultimately boosting the convergence speed of FL training. Moreover, we develop a coordinated approach for uplink receiver beamforming, user selection, and MA positioning to optimize the convergence rate of wireless FL training in dynamic wireless environments. This stochastic optimization challenge is reformulated into a mixed-integer programming problem by utilizing the training loss upper bound. We then introduce a penalty dual decomposition (PDD) method to solve the mixed-integer mixed programming problem. Experimental results indicate that incorporating MA techniques significantly accelerates the training convergence of FL and greatly surpasses conventional methods.
An Overview on IRS-Enabled Sensing and Communications for 6G: Architectures, Fundamental Limits, and Joint Beamforming Designs
Authors: Xianxin Song, Yuan Fang, Feng Wang, Zixiang Ren, Xianghao Yu, Ye Zhang, Fan Liu, Jie Xu, Derrick Wing Kwan Ng, Rui Zhang, Shuguang Cui
Date: 2024-11-11 00:00:00
Tasks: Integrated sensing and communication, ISAC, parameter estimation

This paper presents an overview on intelligent reflecting surface (IRS)-enabled sensing and communication for the forthcoming sixth-generation (6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication (S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's (BS's) non-line-of-sight (NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication (ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.
Linear Receive Beamforming for CAPA Systems
Authors: Chongjun Ouyang, Zhaolin Wang, Xingqi Zhang, Yuanwei Liu
Date: 2024-11-10 00:00:00
Tasks: Form

The performance of linear receive beamforming in continuous-aperture array (CAPA)-based uplink communications is analyzed. Three continuous beamforming techniques are proposed under the criteria of maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-squared error (MMSE). \romannumeral1) For \emph{MRC beamforming}, a closed-form expression for the beamformer is derived to maximize per-user signal power. The achieved uplink rate and mean-squared error (MSE) in detecting received data symbols are analyzed. \romannumeral2) For \emph{ZF beamforming}, a closed-form beamformer is derived based on channel correlation to eliminate interference. As a further advance, its optimality in maximizing effective channel gain while ensuring zero inter-user interference is proven. \romannumeral3) \emph{MMSE beamforming} is established as the optimal linear receive approach for CAPAs in terms of maximizing per-user rate and minimizing MSE. Closed-form expressions are derived for the MMSE beamformer and the achievable sum-rate and sum-MSE. It is mathematically proven that all proposed beamformers lie within the signal subspace spanned by users' spatial responses. Numerical results demonstrate that CAPAs outperform conventional spatially-discrete arrays (SPDAs) by achieving higher sum-rates and lower sum-MSEs under the proposed linear beamforming techniques.
Distributionally Robust Adaptive Beamforming
Authors: Shixiong Wang, Wei Dai, Geoffrey Ye Li
Date: 2024-11-10 00:00:00
Tasks: subspace methods

As a fundamental technique in array signal processing, beamforming plays a crucial role in amplifying signals of interest (SoI) while mitigating interference plus noise (IPN). When uncertainties exist in the signal model or the data size of snapshots is limited, the performance of beamformers significantly degrades. In this article, we comprehensively study the conceptual system, theoretical analysis, and algorithmic design for robust beamforming against uncertainties in the assumed snapshot or IPN covariances. Since such robustness is specific to the probabilistic uncertainties of snapshots or IPN signals, it is referred to as distributional robustness. Particularly, four technical approaches for distributionally robust beamforming are proposed, including locally distributionally robust beamforming, globally distributionally robust beamforming, regularized beamforming, and Bayesian-nonparametric beamforming. In addition, we investigate the equivalence among the four technical approaches and suggest a unified distributionally robust beamforming framework. Moreover, we show that the resolution of power spectra estimation using distributionally robust beamforming can be greatly refined by incorporating the characteristics of subspace methods, and hence, the accuracy of IPN covariance reconstruction can be improved, especially when the interferers are close to the SoI. As a result, the robustness of beamformers based on IPN covariance estimation can be further enhanced.