This article demonstrates an unexplored relay operating mode in Bluetooth Low Energy (BLE)-based Wireless Sensor Networks, enabled by the link-layer synchronization inherent to BLE periodic advertisements. This synchronization allows relay nodes to avoid the power-hungry 100% duty primary-channel scanning that conventional passive BLE receivers rely on for reliable packet capture. To translate this insight into practice, we present the design and implementation of Dynamic Primary-Channel Scanning (DPCS), a practical strategy that disables primary-channel scanning after periodic synchronization and autonomously re-enables it upon synchronization loss, thereby allowing relay nodes to remain asleep for most of their lifetime while still forwarding data on scheduled secondary-channel receptions. We integrate DPCS into a multi-hop, chain-based data propagation framework for linear BLE-based WSNs, where sensor nodes themselves act as relays and forward concatenated data hop-by-hop toward a sink. Enabled by the innate properties of the periodic advertising mechanism, DPCS is directly deployable on commercial off-the-shelf (COTS) BLE 5.x devices as an application-level control logic using the provisions of the BLE stack. Experiments with nRF52832-based nodes in five-node chains demonstrate over 99% per-hop data reception reliability indoors across 50–60 m with modest retransmissions. In outdoor deployments, the per-hop reliability consistently remains above 99% without retransmissions across a 180–200 m span, with rapid automatic re-synchronization after interruptions. Power profiling shows consistently lower energy consumption than both continuous and duty-cycled primary-channel scanning baselines, with up to two to three orders of magnitude savings over continuous scanning at a sensing interval of 60 s. This chain-based analysis provides a baseline for extending the proposed periodic-advertising-based relay operation to more complex network topologies.

In Wireless Sensor Networks (WSNs) involving frequent transmission of large sensor data, packet collisions degrade the performance and add to the energy consumption of the sensor nodes since they require additional packet retransmissions to compensate data loss. In this paper, applications like livestock health monitoring systems have been targeted that involve frequent transmission of large sized motion data sampled along multiple axes. We choose low power non-connectable Bluetooth Low Energy (BLE) extended advertisements for quick transmission of large sensor data, and propose a non-connectable BLE advertising based polling algorithm for eliminating packet collision. Contrary to the existing polling-based schemes that are implemented at the link layer, this is the first work to propose a broadcast-based polling algorithm for the "application" layer. This facilitates its adaptability with commercially available BLE chips in practical deployments, since it runs on top of the standardized BLE link layer that does not implement carrier sensing. It has been shown through real-world experimentation carried out using nRF52832 and nRF52840 SoCs for 5 days, that the proposed polling technique is more effective in networks with higher transmission rates. In a network of 25 nodes transmitting 3,600 bytes every 30 s, with two packet re-transmissions, polling achieves a consistent data delivery success rate between 98-99%, as opposed to nearly 95% achieved without polling in higher (three) re-transmissions. Higher packet delivery rates are achievable in fewer re-transmissions with polling, thus saving power of the sensor nodes.

Recent advancements in Bluetooth Low Energy (BLE) have made it a promising solution for delay-sensitive and energy-constrained IoT applications, such as robotic automation in industrial settings. However, existing BLE service architectures, namely the BLE beacon-to-user and beacon-gateway-server-user models, either suffer from high delays, unreliable performance, or a reliance on internet connectivity, which is often limited in environments such as underground parking areas, airports, and supermarkets. Additionally, these architectures use BLE legacy advertising, which offers limited throughput and thus contributes to further delays. To address these limitations, this paper proposes a novel BLE-centric enhanced service architecture that minimizes the delay experienced by users and enhances the energy efficiency of BLE beacons. Based on the proposed service architecture, we first develop an analytical model to evaluate delay and then derive simplified closed-form expressions for selecting optimal transmission parameters. These parameters minimize the delay experienced by users and improve the energy efficiency of BLE beacons. The proposed architecture also leverages BLE extended and periodic advertising modes, which offer higher throughput, thereby further reducing delay and improving overall performance. Additionally, lightweight algorithms are introduced to adapt these parameters dynamically based on network conditions. The proposed model is validated through simulations, showing strong agreement with the analysis and confirming its practical effectiveness.

Bluetooth low energy (BLE) allows connectionless data transfer to take place through advertisements. Bluetooth Core Specification version 5.0 introduced extended advertising which allows each secondary channel advertising packet to carry up to 255 bytes of payload. Up to 1650 bytes of data can be advertised as a single transmission through chaining of multiple packets carrying fragments of advertising data. This article derives throughput expression in the presence of bit errors and analyses the maximum throughput for connectionless data transfer using extended advertisements, for all the Uncoded and Coded PHYs that offer different data rate and range capabilities. Guidelines are provided for the choice of appropriate PHYs based on the transmission size, throughput, and range requirement of the application. Simulation results have been presented that verify the analytically obtained throughput values. Since connectionless mode of communication does not allow acknowledgments from the receiver, it is essential to overcome the impact of bit errors through retransmission of each packet for increased chances of its reception. Analysis of maximum achievable throughput with retransmission of each data packet has also been presented in this article. Results suggest that the maximum achievable throughput is impacted by the duration of each transmission, due to which beyond a certain value of the data size, the low energy (LE) Coded PHYs are unable to offer significant improvement in the amount of data delivered per unit time.

In this paper, design of a BLE periodic advertising based data logger for cold chain temperature monitoring has been proposed, which is implemented using multi-threading on a Real Time Operating System for smooth, unhindered operation. The low-power logger design only implements the data fetching, storing and transmission operations, and the logged data can be accessed on a smartphone app using BLE periodic advertisements, through a simple button press, as many times as required to achieve 100% reception in the app. The data processing capabilities are implemented in the smartphone app and not the device to save power. Data transmission consumes ultra low current by the use of BLE periodic advertisements, which are experimentally shown in this paper to consume an average current of only 99.3 µA for transmitting the data logged over 24 hours. Additionally, even without entering into a connection, the data reception using BLE periodic advertising has been experimentally found to be in the range 96–98 % due to its ability to synchronize with the receiver, and the use of secondary advertising channels for data transfer. We have developed a smartphone app that implements a BLE periodic scanner, and allows the user to successfully receive 100% of the logged data, save it to the device/cloud and export the data anomalies based on the ambient range of values provided.

Modbus protocol is widely used in industrial automation, that allows the transfer of sensor data to take place over a serial interface, using a request-response framework. However, the deployment of Modbus relies on cabling and its scalability is restricted. In this paper, we propose an industrial automation framework that uses the low power connection-less mode of Bluetooth Low Energy to transfer data from the sensor nodes to a central Gateway using extended advertisements, and uses Modbus to relay the sensor data to the main supervisory unit. The Gateway stores all the packets received from the end nodes in a local storage, which is accessed each time a Modbus request for the data of a particular node is received. The paper proposes a customized wired data exchange algorithm developed on top of the standard Modbus RTU protocol, and efficient memory access (read/write) algorithms that ensure quick fetching of the sensor data from the storage at the Gateway corresponding to each Modbus request, making the response time independent of the size of the sensor network. We have provided real-time experimental results to show the high reception rates (94-100%) of sensor data transmitted using BLE extended advertisements in dense deployments, quick responsiveness of the Gateway (almost constant request-response time of 250 ms approximately), and the successful reception of sensor data at the supervisory unit using the proposed framework.

IoT applications like livestock and personalized health care monitoring systems have large amounts of data obtained per second from sensors interfaced to battery operated sensor nodes. In such networks, all the data generated at the nodes must be successfully sent to the central receiving device ensuring minimal power consumption of the data transmission operation, to enable longer lifetimes of battery-operated sensor nodes. In this article, in order to minimize energy consumption of sensor nodes, we propose a Bluetooth low energy (BLE)-based data transfer approach relying on BLE periodic advertisements, which allow up to 255 bytes of payload to be sent in one packet and minimize the involvement of interference prone primary advertising channels in the data transfer process. By using primary channel transmissions only for one-time device discovery and then disabling them, the proposed technique ensures that number of transmissions made by each sensor node for successful data delivery in large sensor networks is reduced in comparison with conventional extended and periodic advertisements. This offers reduction in energy consumption of sensor nodes due to reduction in radio on time. Through extensive real-time and simulation-based experimentation conducted, we have shown that, in a network of 200 sensor nodes, the proposed periodic advertising-based technique requires much lesser radio on time for reliable data delivery and reduces energy consumption of the sensor nodes by almost 51% and 20% as compared to the consumption when extended and standardized periodic advertisements are used to communicate the data, respectively.

Bluetooth Low energy (BLE) advertisements have great potential in Internet of Things applications like monitoring systems, which involve the real-time transfer of data collected from sensors interfaced to multiple power-constrained devices. Since sensor data conveys information about the present state of the system, packet loss is vital in such applications. The paper proposes a customized BLE legacy advertising packet structure to advertise dynamic sensor data, and proposes two techniques: One-Set-Multiple-Events (OSME) and One-Set-X-Events (OSXE), to advertise the dynamic sensor data using the non-connectable and non-scannable undirected advertising mode of BLE. Using appropriate advertising parameters with OSXE, each advertising packet gets successfully advertised$X$times, whereas OSME neither guarantees successful advertisement of all the packets, nor does it allow control over the number of transmitted copies of each packet. Using OSXE, experimental analysis is carried out to study packet loss when single BLE node transmits alone, and when 25 nodes transmit simultaneously. Mathematical analysis has been carried out for packet collision for multiple nodes. Experimental results show that packet loss is also impacted by factors like advertising set duration, scan window, scanner's link layer activities like advertising report generation and channel switching. Using OSXE, packet loss close to 0% is obtained for$X=3$when 25 nodes advertise simultaneously.

The network connectivity while traveling in a vehicle is an important issue, which needs to be addressed by mobile vehicular networks. This paper proposes a novel scheme to improve the connectivity of mobile vehicular networks. In particular, the paper proposes a medium access control (MAC) layer hybrid mmWave and microwave scheme for vehicular networks, and leverage their capabilities to improve the vehicle’s connectivity. The novel computational model is derived to evaluate the connectivity for the proposed scheme. The model is used for performance analysis of vehicles moving on a multi-lane highway road and getting connectivity with road-side-units (RSUs) deployed along the roads. Our analysis considers that reference VN has perfect channel state information. It is assumed that the RSU radiates ubiquitously on the road surface using microwave radio access technology (RAT), while it radiates directionally towards reference VN using mmWave RAT. For mathematical analysis, the directionality in mmWave RAT is well approximated by a sectored antenna model. The analysis for the proposed scheme is compared with the existing mmWave network and packet data convergence protocol (PDCP) layer hybrid scheme. The analysis claims that the proposed hybrid scheme significantly improves the connectivity performance in mobile vehicular networks over the existing schemes. The computation results are validated with the simulation results. Also, the paper offers parametric analysis for connectivity probability with vehicle speed and slot duration to enable its practical implementation in 5G/6G technologies.

Autonomous Vehicles (AVs) rely on a set of radar sensors operated on frequency modulated waveforms. Due to the large bandwidth requirement of frequency modulated radars, only a limited number of proximate vehicles can be allowed for a concurrent transmission within the available spectrum. However, with the explosive growth of AVs, the available spectrum may soon reach its capacity. As a results, the coexistence of multiple AVs working on same resource, may lead to the problem of Radar-to-Radar (R2R) interference, also known as radar blindness. In this paper, we propose the notion of coded waveforms to minimize the R2R interference among the vehicles operating on the same resource. Specifically, the spread spectrum codes have been used as another degree of freedom (i.e., along with time-frequency resources) to spread the inter-vehicular radar interference over the wider spectrum, which enable to orthogonalize more number of AVs over the available range of spectrum. In addition, we have formulated a Spread Spectrum-based Radar Transmission Scheme (SS-RTS), and described the transmission and reception through SS-RTS. Also, the SS-RTS has been compared with the existing Graph-based Resource Allocation (GRA) scheme. Further, simulation results verified that SS-RTS significantly reduces the inter-vehicular R2R interference and outperforms GRA in terms of blind probability.

Autonomous Vehicles (AVs) rely on a set of radar sensors used to map surrounding environment. Most commonly used radar sensors for AVs use Frequency Modulated Continuous Wave (FMCW) ramps for object parameter (i.e., range and relative velocity) estimation. Due to large bandwidth requirement of FMCW radar, only a limited number of AVs can be operated in the available spectrum. Consequently, the co-existence of large number of AVs may lead to the problem of radar-to-radar interference, also referred to as radar blindness. Moreover, the problem becomes more severe in the higher traffic scenarios. In this work, we propose a Traffic-based Adaptive Ramp Packing (TRAP) scheme, which adapts radar range and assigns FMCW ramp parameters on the basis of inter-vehicular distance among AVs. Specifically, TRAP scheme allows to make effective use of the available time-frequency resource, and enables to pack more ramps in the dense traffic scenarios. Further, it is shown that adaptive radar range adoption may provide significantly more number of ramps in the given bandwidth. Furthermore, through simulation results, it is shown that TRAP significantly reduces the blind probability against state-of-the-art fixed range schemes.