Ultra-Low-Power Wide Range Backscatter Communication Using Cellular Generated Carrier †

In this book chapter, we give an overview of transmission techniques applied for application developments in smart cities. In the perspectives of technologies, we consider possible system models together with performance system analysis. Subsequently, we introduce various potential technologies and their current analytical results. These main techniques are studied to improve system performance at destinations. We first consider backscatter communication, reconfigurable intelligent surfaces, physical layer security, etc. Because of advantages of these technologies, some candidates of transmission techniques are expected to outperform the existing wireless communication systems regarding the outage probability, ergodic capacity, transmission rate, and throughput. Finally, we recommend to deploy backscatter communication in transmission from the base station to users (or sensor nodes) in applications in smart cities; for example, the outage performance of two destinations in the downlink cellular network by taking advantage of NOMA and backscatter communication.KeywordsAmbient backscatterPhysical layer securityReconfigurable intelligent surfaceNon-orthogonal multiple access5G6G

Backscatter communication (BC) has emerged as a pivotal wireless communication paradigm owing to its low-power and cost-effective characteristics. However, BC faces various challenges from its low signal detection rate to its security vulnerabilities. Recently, reconfigurable intelligent surfaces (RIS) have surfaced as a transformative technology addressing power and communication performance issues in BC. However, the potential of RIS in addressing the security challenges of BC remains uncharted. This paper investigates the secrecy performance of RIS-aided BC, where all channels are distributed according to the Fisher-Snedecor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {F}$</tex-math></inline-formula> distribution. Specifically, we consider a RIS with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> reflecting elements to help a backscatter device (BD) establish a smart environment and enhance the secrecy performance in BC. Due to the nature of BC systems, our analysis considers two possible scenarios (i) in the absence of direct links and (ii) in the presence of direct links. In both cases, we first derive compact analytical expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the received signal-to-noise ratio (SNR) at both a legitimate receiver and an eavesdropper. Then, to analyze the secrecy performance, we further derive analytical expressions of the average secrecy capacity (ASC) and secrecy outage probability (SOP) for both mentioned scenarios. In addition, regarding the importance of system behavior in a high SNR regime, we provide an asymptotic analysis of the SOP and ASC. Eventually, the Monte-Carlo simulation is used to validate the analytical results, revealing that utilizing RIS can greatly improve the secrecy performance of the BC system relative to traditional BC setups that do not incorporate RIS.

Non-orthogonal multiple access (NOMA) is becoming one of the promising technologies for the fifth generation (5G) and beyond 5G (B5G) communications due to its ability of connecting massive wireless devices. Meanwhile, backscatter communication (BSCom) is emerging as a key solution to the Internet of Things (IoTs) due to its energy efficiency. In this chapter, we first provide a brief introduction of NOMA technology, discuss its fundamental concepts, and outline its applications. Then, we discuss the basic concepts of BSCom systems in brief, describe its different configurations, highlight the challenges of NOMA-enabled BSCom systems, and discuss the recent solutions. Moreover, we provide the basics of physical layer security (PLS) in wireless communication systems. Using the aforementioned backgrounds, we formulate an optimization problem for secrecy rate maximization in NOMA-enabled BSCom in the presence of multiple eavesdroppers. The problem is subjected to backscatter device (BSD) reflection coefficient and base station (BS) power according to NOMA protocol. To efficiently solve the optimization problem, we exploit the duality theory. For the purpose of comparison, we also present a conventional orthogonal multiple access (OMA)-enabled BSCom system as a benchmark. Finally, we present the simulation results and conclude this chapter with future research directions.

The proliferation of Internet of Things (IoT) devices has opened new roads for collaborative distributed applications, particularly in smart city environments, where a variety of resources, including sensing, actuation, computation, and storage, are essential for providing effective location-based services. This paper specifically focuses on the sharing of heterogeneous resources among IoT applications in smart cities. By leveraging game-theoretic principles, this study addresses resource allocation through a combinatorial double auction. The solution is rooted in the concept of Social IoT (SIoT), where Internet-connected objects create dynamic social networks based on rules set by their owners. Social relationships, such as ownership and co-location, are leveraged to form groups offering enhanced reliability resource bundles. The proposed solution offers several key economic properties, including incentive compatibility, individual rationality, and a balanced budget, while maintaining low computational complexity. Simulation results demonstrate that the proposed combinatorial double auction mechanism achieves over 70% successful resource allocation for up to 1000 requests, maintains computational efficiency with execution times under 30 s, and ensures economic properties such as incentive compatibility and individual rationality, making it a scalable and practical solution for large-scale smart city IoT applications.

Backscatter communication is a new wireless communication technology, which can enable battery-free devices to communicate with others by backscattering ambient radio-frequency signals, and therefore has great potential to be deployed in the future Internet of Things (IoT) networks. In the existing related studies, the adopted centralized approach might be not suitable for a large-scale IoT network with sporadic backscatter communication, while the adopted distributed approach ignored the demand of the access point (AP). In this paper, we consider a large-scale IoT network consisting of the legacy Wi-Fi communication and the backscatter communication, and aim to propose an efficient distributed backscatter medium access control protocol that takes into account of the demand of the AP. In our protocol, when the AP has a demand to collect the information of backscatter devices, it enables backscatter devices to contend for the channel with Wi-Fi devices in a separate manner, where the backscatter devices are only allowed to participate in the contention in a limited time period. We then characterize this constrained contention process and develop a theoretical model to analyze the performance of the proposed protocol. With this model, we can exactly express the per-node throughput of Wi-Fi and backscatter devices. Finally, extensive simulations verify that our model is much accurate, and our protocol can outperform the related protocol in terms of both per-node throughput and system throughput.

Abstract: Radio-over-Free-Space Optics (RoFSO) systems have emerged as a promising solution to address the growing demand for high-capacity and flexible wireless communications in smart city environments. RIS-assisted RoFSO systems offer a compelling solution to the communication challenges inherent in smart city applications. By leveraging the reflective and reconfigurable capabilities of intelligent surfaces, these systems can overcome the traditional LOS limitations and significantly mitigate the adverse effects of atmospheric turbulence, as accurately modeled by the Málaga-M distribution. The demonstrated improvements in outage probability, channel capacity, and bit error rate highlight their potential to provide reliable, high-speed, and flexible wireless connectivity in dense urban environments. However, the performance of RoFSO links is significantly affected by atmospheric turbulence. The Málaga-M distribution has gained prominence as a comprehensive model to capture a wide range of turbulence conditions. Recent advancements in Reconfigurable Intelligent Surfaces (RISs) offer a new dimension to mitigating the limitations of FSO channels. This paper provides a comprehensive literature review on the integration of RIS with RoFSO systems over Málaga-M fading, focusing on their applicability in smart city deployments.

Smart cities have expanded rapidly with the introduction of Internet of Things (IoT) devices and edge computing techniques. Such technologies have transformed how cities function through the ability to deliver smart services and analyze data in real time. But that advancement also adds to the demanding issues about privacy and data security. In smart city environments, privacy-preserving is essential to protect sensitive data collected from different channels against leakage, abuse and unauthorized access. This work is a review of data security and privacy-preserving models made for edge computing and smart cities. It examines the advantages and disadvantages of existing machine learning, blockchain, cryptography, hybrid architectures of optimizing resources, scalability and efficiency. The review discusses open challenges, including interoperability, resource constraints and governance issues, as well as future research directions such as quantum-secure security, federated learning and AI-based adaptive models. The concepts aim to help researchers and policymakers establish strong, durable smart city infrastructures.

In this paper, we propose a novel integrated sensing and backscatter communication (ISABC) system in which each moving target is attached with a backscatter device (BD) to facilitate simultaneous target identification and parameter estimation. When the base station (BS) transmits signals to its desired user, each BD attached to the target transmits the target identification information to the BS via backscatter communication, which concurrently enhances the echo signal strength. The BS needs to detect the BD symbols and to estimate the target parameters using the echoes. This task, however, is challenging due to the coupling between the BD symbols and the target parameters. To address this issue, we propose a novel iterative detection and estimation (IDE) framework, which involves the following two processes alternately: 1) Utilizing a modified maximum likelihood (ML) estimator to perform parameter estimation with the detected BD symbols; 2) Employing the ML detector to detect the BD symbols with the estimated target parameters. Since the inter-carrier interference (ICI) of the OFDM signal is independent of the BD symbols, but contains the delay and Doppler shift information, we develop a target parameter initialization method using such ICI component to improve the performance of the proposed IDE scheme. Moreover, the closed-form Miller-Chang bound is derived to demonstrate the theoretical performance for the target parameter estimation. Finally, simulation results are provided to validate the effectiveness of the proposed designs.

In this developing paradigm, heterogeneous network infrastructure is combined with ubiquitous devices for sensing, smart control systems and big data analytics to create “smart cities.” Enhancing the overall quality of life is one of their main goals and they do so through smart services they offer in a broad range of areas such as transportation, healthcare, entertainment (including virtual reality), the environment (including pollution) and energy. To be able to offer those services, the job of big data and their analysis is complicated, since it allows for the extraction of useful insights from the enormous amounts of data that the smart cities produce. The current state-of-the-art research efforts aimed at big data analytics in a smart city setting are investigated and presented in this chapter. In particular, a comprehensive literature review on the big data analytic frameworks for smart cities is provided. Following that, a short talk on IoT and big data is briefed. Owing to different data that the smart cities collect, which frequently have contradictory processing needs, appropriate investigative methods based on the data type are also recommended, depending on the data type. The many smart city applications were investigated and a perspective on the difficulties associated with smart city development was developed. In this chapter, the methods addressing the smart city issues and development are examined, and the possibility for the employment of integrated IoT and big data analytics is presented. Finally, as a case study, a briefing on a call service application for the fire department in a smart city is provided to round up the presentation.

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

Wireless brain-computer interfaces (BCIs) are highly energy constrained because of the need to minimize battery size and weight, as well as the need to minimize the thermal dissipation into the living tissue. We demonstrate an ultralow-power Bluetooth Low Energy (BLE) v5.0 compatible backscatter communication uplink for the NeuroDisc BCI. This backscatter approach is compatible with completely unmodified BLE devices such as PCs, smartphones, and tablets and has an energy consumption of under 200 pJ/bit, over 50× less than commercially available BLE transmitters. This article is the first to present an analysis and demonstration of single sideband (SSB) BLE backscatter, which increases the available channel power by +3 dB while suppressing out-of-channel emissions. An analytic model of SSB backscatter communication is provided, along with simulations showing how nonidealities in the achieved backscatter constellation impact opposite-sideband suppression. The experimental measurements of in-channel gain and opposite-sideband suppression are provided. Additional experiments demonstrate a range of 6 m using a +20-dBm external carrier source and an unmodified Nordic Semiconductor nRF51DK BLE adapter, while uplinking prerecorded neural data sampled at 500 Hz.

This paper proposes a photorealistic 3D city simulation method for training autonomous vehicles. The proposed method incorporates human simulation, animal simulation, vehicle simulation, and traffic light simulation. To generate natural actions for humans and animals, a motivation-based approach is first applied; then the Q-Network is used to select optimal goals depending on the motivations, and action plans are made based on a hierarchical task network. For vehicles, affinity propagation, data augmentation, and convolutional neural network are employed to generate driver driving data for realistic vehicle movement simulation. A traffic light system is also implemented based on rules derived from real-life observation. The results of experiments in which a virtual city was created demonstrate that the proposed method can simulate city environments naturally. The proposed method can be applied to various smart city applications, such as autonomous vehicle training systems.

Protect your data and I’ll rank its utility: A framework for utility analysis of anonymized mobility data for smart city applications

In conventional backscatter communication (BackCom) systems, various centralized access schemes, i.e., time/frequency division multiple access, are commonly adopted to prevent transmission collisions among multiple backscatter devices (BDs). However, as the number of BDs proliferates, there will be high overhead, and more seriously, the proactive inter-user coordination may be unaffordable for the passive BDs, which are of scarce concern in existing works and remain a challenge to solve. To this end, in this paper, we propose a slotted ALOHA-based random access for multi-BD BackCom systems, where each BD is selected randomly and coexists with an active device for hybrid transmission. To excavate and evaluate the performance, a resource allocation problem targeting max-min average throughput is formulated, where transmit antenna selection, receive beamforming design, reflection coefficient (RC) adjustment, power control, and access probability determination are jointly optimized. To deal with this intractable problem, we first transform the objective function with the max-min form into an equivalent linear one, and then decompose the resulting problem into three sub-problems. Next, a block coordinate descent-based greedy algorithm, incorporating maximum ratio combining, semi-definite programming, and variable substitution, to achieve a sub-optimal solution. Besides, we derive closed-form solutions for both RC and transmit power to facilitate analysis. Simulation results demonstrate that the proposed algorithm outperforms benchmark algorithms in terms of throughput and fairness.

The deployment of fifth-generation (5G) wireless networks has already laid the ground-work for futuristic smart cities but along with this, it has also triggered the rapid growth of a wide range of applications, for example, the Internet of Everything (IoE), online gaming, extended/virtual reality (XR/VR), telemedicine, cloud computing, and others, which require ultra-low latency, ubiquitous coverage, higher data rates, extreme device density, ultra-high capacity, energy efficiency, and better reliability. Moreover, the predicted explosive surge in mobile traffic until 2030 along with envisioned potential use-cases/scenarios in a smart city context will far exceed the capabilities for which 5G was designed. Therefore, there is a need to harness the 6th Generation (6G) capabilities, which will not only meet the stringent requirements of smart megacities but can also open up a new range of potential applications. Other crucial concerns that need to be addressed are related to network security, data privacy, interoperability, the digital divide, and other integration issues. In this article, we examine current and emerging trends for the implementation of 6G in the smart city arena. Firstly, we give an inclusive and comprehensive review of potential 6th Generation (6G) mobile communication technologies that can find potential use in smart cities. The discussion of each technology also covers its potential benefits, challenges and future research direction. Secondly, we also explore promising smart city applications that will use these 6G technologies, such as, smart grids, smart healthcare, smart waste management, etc. In the conclusion part, we have also highlighted challenges and suggestions for possible future research directions. So, in a single paper, we have attempted to provide a wider perspective on 6G-enabled smart cities by including both the potential 6G technologies and their smart city applications. This paper will help readers gain a holistic view to ascertain the benefits, opportunities and applications that 6G technology can bring to meet the diverse, massive and futuristic requirements of smart cities.