Robust Wireless Network Research Articles

An adaptive compressive sensing method on hybrid-field channel estimation for a massive MIMO system

Massive MIMO (Multiple-input-multiple output), crucial for 5 G and Beyond 5 G (B5G) networks, faces challenges with terahertz frequencies in B5G as the communication shifts from far-field to near-field. This shift disrupts traditional Massive MIMO channel estimation, leading to increased pilot overhead and limited performance. The current study used the hybrid-field orthogonal matching pursuit (HF-OMP) algorithm from the compressive sensing (CS) framework to estimate the channel with scatters from both far-field and near-field. The method, however, needs more flexibility regarding scatter location in the field of interest. Also, the usage of HF-OMP under a single measurement vector (SMV) scheme limits the overall performance of the existing method. To address these, we have proposed an adaptive hybrid-field simultaneous-OMP algorithm under multiple measurement vector (MMV) of the CS framework which selects multiple atoms having common support within a single iteration. This innovative approach tackles channel estimation for both far-field and near-field scatters while adapting to their varying distributions. Compared to classical methods, simulations show the new algorithm achieves up to a 14 % improvement in normalized mean square error within a 0 dB to 10 dB signal-to-noise ratio range. This translates to significant reductions in pilot overhead and enhanced channel reliability, paving the way for more efficient and robust wireless networks in the future.

PERFORMANCE ANALYSIS OF DUAL-PARALLEL/DUAL-ELECTRODE MACH-ZEHENDER MODULATOR-BASED RADIO-OVER-FIBER SYSTEM AGAINST THIRD-ORDER INTERMODULATION ERRORS

The rapid development in wireless networks required by mobile and broadband users in terms of capacity, data rate, bandwidth, cost effectivity, green communications, proper quality of service, and so on create the need of a robust system against nonlinear errors. In view of this, the performance of a dual-parallel/dual-electrode Mach-Zehender modulator-based targeted radio-over-fiber (RoF) system for multitone transmission against severe nonlinear errors (i.e., third-order intermodulation) is analyzed. Two-tone radio frequency signals, operating at 9 GHz and 8 GHz, are used in the proposed system. The analytical analysis is confirmed and validated by simulation results using OptSim software. Further, comparative findings are found by considering a conventional Mach-Zehender modulator-based RoF system. The reduction in the third-order intermodulation errors of 21 dB over a fiber distance of 10 km by the proposed method over a conventional system and the obtained results find the implementation of the proposed method to be a robust wireless network.

The Challenge of Long-Distance Over-the-Air Wireless Links in the Ocean: A Survey on Water-to-Water and Water-to-Land MIoT Communication

Robust wireless communication networks are a cornerstone of the modern world, allowing data to be transferred quickly and reliably. Establishing such a network at sea, a Maritime Internet of Things (MIoT), would enhance services related to safety and security at sea, environmental protection, and research. However, given the remote and harsh nature of the sea, installing robust wireless communication networks with adequate data rates and low cost is a difficult endeavor. This paper reviews recent MIoT systems developed and deployed by researchers and engineers over the past few years. It contains an analysis of short-range and long-range over-the-air radio-frequency wireless communication protocols and the synergy between these two in the pursuit of an MIoT. The goal of this paper is to serve as a go-to guide for engineers and researchers that need to implement a wireless sensor network at sea. The selection criterion for the papers included in this review was that the implemented wireless communication networks were tested in a real-world scenario.

Wavelet Generalized Regression Neural Network Approach for Robust Field Strength Prediction

Accurate predictive field strength and coverage modelling during and after cellular network planning process is one key factor that contribute to a successful and robust wireless communication network performance. Accurate field strength coverage prediction will provide realistic idea about the level of field strength and link quality in the entire coverage service areas. It will also assist in close-fitting fringe areas that are likely to be imparted negatively by interference, and cell edge/contour areas with poor signal coverage. Therefore, opting for a suitable predictive field strength system model that will enable superb cellular network planning environment will be of a great succor to the radio network planner and stakeholders, including the network end users as well. This work presents spatial electric field strength prediction engaging hybrid wavelet-neural modelling approach. The proposed is called Wavelet-GRNN. To accomplish this task, the spatial field strength data is first routed through a wavelet-based decomposition process employing three decomposition levels. The decomposed field strength constituents are then utilised as input data to GRNN neural network model where relevant extracted information is captured and trained for robust predictive learning. In the third phase of the model, the outputs from the GRNN predictor are combined with wavelet coefficients to form the final predicted output. The degree of prediction accuracy using the Wavelet-GRNN model over other prediction techniques are also statistically quantified and provided using six different first order statistics.

An Energy-Efficient Multiobjective Scheduling Model for Monitoring in Internet of Things

To ensure robustness in wireless networks, monitoring the network state, performance and functioning of the nodes and links is crucial, especially for critical applications. This paper targets Internet of Things (IoT) networks. In the IoT, devices (things) are vulnerable due to security risks from the Internet. Moreover, they are resource-constrained and connected via lossy links. This paper addresses the optimized scheduling of the monitoring role between the embedded devices in IoT networks. The objective is to minimize energy consumption and communication overhead of monitoring, for each node. Several subsets of the potential monitoring nodes are generated by solving a minimal vertex cover (VC) problem with constraint generation. Assuming periodical functioning, VCs are optimally assigned to time periods in order to distribute the monitoring role throughout the entire network. The assignment of VCs to periods is modeled as a multiobjective generalized assignment problem. To further optimize the energy consumption of the monitors, they are sequenced across time periods to minimize the state transitions of nodes. This part of the problem is modeled as a traveling salesman path problem. The proposed model is tested on randomly generated instances and the experimental results illustrate its effectiveness to optimize the scheduled monitoring for fault tolerance in IoT networks.

AODV routing protocol for Cognitive radio access based Internet of Things (IoT)

Proactive based RPL is the network layer routing protocol designed for route-discovery to transmit the constrained application data from leaf nodes (LLN) to the LLN boarder router (LBR). From LLN boarder router (LBR) to the destination that is connected to non-constrained networks, traditional wired or wireless network is used to transmit the application data. Due to the flexibility and robustness of wireless networks, it can be used to transmit the application data from LBR to non-constrained networks. Opportunistic access based cognitive radio networks can be the most promising networking technology to transmit the constrained IoT data opportunistically in licensed PU free channels from LLN-LBR to the non-constrained networks. In this paper, hybrid control channel based cognitive AODV routing protocol with directional antennas is proposed to discover the channel-route from the LBR to the destination that is connected within the Cognitive Radio Networks. Experimental results reveal that the proposed cognitive AODV protocol with directional antennas is outperformed in comparison with traditional Infrastructure based wireless networks.

An efficient genetic algorithm for large-scale transmit power control of dense and robust wireless networks in harsh industrial environments

The industrial wireless local area network (IWLAN) is increasingly dense, due to not only the penetration of wireless applications to shop floors and warehouses, but also the rising need of redundancy for robust wireless coverage. Instead of simply powering on all access points (APs), there is an unavoidable need to dynamically control the transmit power of APs on a large scale, in order to minimize interference and adapt the coverage to the latest shadowing effects of dominant obstacles in an industrial indoor environment. To fulfill this need, this paper formulates a transmit power control (TPC) model that enables both powering on/off APs and transmit power calibration of each AP that is powered on. This TPC model uses an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects, to enable accurate yet simple coverage prediction. An efficient genetic algorithm (GA), named GATPC, is designed to solve this TPC model even on a large scale. To this end, it leverages repair mechanism-based population initialization, crossover and mutation, parallelism as well as dedicated speedup measures. The GATPC was experimentally validated in a small-scale IWLAN that is deployed a real industrial indoor environment. It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC. Moreover, sensitivity analysis was performed to reveal the produced interference and the qualification rate of GATPC in function of varying target coverage percentage as well as number and placement direction of dominant obstacles.

Unpredictable cryptographic primitives for the Robust Wireless Network Security

A robust stream cipher algorithm is defined as unpredictable and random generator of the keystreams under minimal perturbations over its inputs. It provides too strong encryption resisting to the attacks founded on the correlation of the regenerated keystreams. The robustness of a wireless network security requires efficient cryptographic primitives and security protocols able to prove the integrity, authentication and confidentiality of the sensitive information. In this paper, we aim to enhance the data confidentiality and integrity of the wireless network. To highlight the data integrity, we introduce a dynamic integrity check code that calculates a checksum from primitive polynomials generator. In our contribution, we focus on the dynamist, unpredictability and non-traceability of sensitive information. We progress our system by a process of regeneration of the primitive polynomials proper to any communication session without touching the internal behavior of the habitual systems. We aim also to introduce a solution which influences by any minimal perturbation on the sensitive elements. It inspires its robustness by its aptitude to regenerate lightweight, dynamic and robust cryptographic primitives able to ensure robust wireless network security.

System Control Applications of Low-Power Radio Frequency Devices

This paper conceptualizes a low-power wireless sensor network design for application employment to reduce theft of portable computer devices used in educational institutions today. The aim of this study is to design and develop a reliable and robust wireless network that can eradicate accessibility of a device’s human interface. An embedded system supplied by an energy harvesting source, installed on the portable computer device, may represent one of multiple slave nodes which request regular updates from a standalone master station. A portable computer device which is operated in an undesignated area or in a field perimeter where master to slave communication is restricted, indicating a possible theft scenario, will initiate a shutdown of its operating system and render the device unusable. Consequently, an algorithm in the device firmware may ensure the necessary steps are executed to track the device, irrespective whether the device is enabled. Design outcomes thus far indicate that a wireless network using low-power embedded hardware, is feasible for anti-theft applications. By incorporating one of the latest Bluetooth low-energy, ANT+, ZigBee or Thread wireless technologies, an anti-theft system may be implemented that has the potential to reduce major portable computer device theft in institutions of digitized learning.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network – Performance evaluation

Connected Vehicle Technology (CVT) requires wireless data transmission between vehicles (V2V), and vehicle-to-infrastructure (V2I). Evaluating the performance of different network options for V2V and V2I communication that ensure optimal utilization of resources is a prerequisite when designing and developing robust wireless networks for CVT applications. Though dedicated short range communication (DSRC) has been considered as the primary communication option for CVT safety applications, the use of other wireless technologies (e.g., Wi-Fi, LTE, WiMAX) allow longer range communications and throughput requirements that could not be supported by DSRC alone. Further, the use of other wireless technology potentially reduces the need for costly DSRC infrastructure. In this research, the authors evaluated the performance of Het-Net consisting of Wi-Fi, DSRC and LTE technologies for V2V and V2I communications. An application layer handoff method was developed to enable Het-Net communication for two CVT applications: traffic data collection, and forward collision warning. The handoff method ensures the optimal utilization of available communication options (i.e., eliminate the need of using multiple communication options at the same time) and corresponding backhaul communication infrastructure depending on the connected vehicle application requirements. Field studies conducted in this research demonstrated that the use of Het-Net broadened the range and coverage of V2V and V2I communications. The use of the application layer handoff technique to maintain seamless connectivity for CVT applications was also successfully demonstrated and can be adopted in future Het-Net supported connected vehicle applications. A long handoff time was observed when the application switches from LTE to Wi-Fi. The delay is largely due to the time required to activate the 802.11 link and the time required for the vehicle to associate with the RSU (i.e., access point). Modifying the application to implement a soft handoff where a new network is seamlessly connected before breaking from the existing network can greatly reduce (or eliminate) the interruption of network service observed by the application. However, the use of a Het-Net did not compromise the performance of the traffic data collection application as this application does not require very low latency, unlike connected vehicle safety applications. Field tests revealed that the handoff between networks in Het-Net required several seconds (i.e., higher than 200ms required for safety applications). Thus, Het-Net could not be used to support safety applications that require communication latency less than 200ms. However, Het-Net could provide additional/supplementary connectivity for safety applications to warn vehicles upstream to take proactive actions to avoid problem locations. To validate and establish the findings from field tests that included a limited number of connected vehicles, ns-3 simulation experiments with a larger number of connected vehicles were conducted involving a DSRC and LTE Het-Net scenario. The latency and packet delivery error trend obtained from ns-3 simulation were found to be similar to the field experiment results.

Some wireless challenges

Wireless networks are now essential to the day-to-day operation of schools. Gill Tica looks at the challenges schools face in setting up a robust wireless network and offers some advice on getting your network right

Seizing the Mobile Moment: Spectrum Allocation Policy for the Wireless Broadband Century

Broadband is widely recognized as a key platform for enabling and supporting job creation, economic development, and innovation in both the short- and long-terms. Many recent policy debates have focused on spurring the deployment of wired broadband networks to unserved parts of the country. While important, these discussions largely overlook the vital role that wireless broadband is playing and will continue to play in delivering critical services and applications to a variety of end-users. This article analyzes the current state of the marketplace and assesses how a variety of sectors of the economy - healthcare, energy, education, and public safety - are leveraging ubiquitous and robust wireless broadband networks to deliver cutting-edge new tools. In order to sustain such high levels of innovation and competition, innovators will require additional spectrum resources to ensure that wireless networks are reliable and capable of providing fast transmission speeds. As such, this article provides an analysis of how the Federal Communications Commission has historically apportioned spectrum and draws best practices for use in today’s marketplace. In an effort to prevent a spectrum shortage and provide policymakers with guidance as they approach these issues, this article concludes by articulating a series of recommendations for use by policymakers. Combined with the best practices, these policy recommendations seek to ensure meaningful policy making as stakeholders aim to position the wireless sector for continued success.

Speeding up column generation for robust wireless network planning

The wireless network planning problem consists of base station placement and traffic node assignment to base stations. To incorporate traffic demand uncertainties, we follow the Γ -robustness approach by Bertsimas and Sim. In this paper, we develop a branch-and-price algorithm, with the aim to enhance the solution process and improve the dual bounds. Instead of assigning individual traffic nodes to base stations, subsets of traffic nodes are assigned to a base station, implying that the pricing problem essentially is a robust knapsack. Since a straightforward implementation does not give satisfactory results, we present techniques, which we apply to the master problem as well as to the pricing problems, to improve the performance. We investigate the effectiveness of these techniques in an extensive computational study.

Near Real Time Network Simulation for Team Sports Monitoring

On field monitoring of athlete performance is a growing area of interest in elite, professional and even some amateur sports. Metrics routinely monitored can be tactical, physiological and biomechanical, some methods are more labor intensive than others such as bloods and video coded and hand scored performance data. More recently the introduction of wearable sensors and GPS have allowed comparatively large amounts of data to be collected. These sensors are changing the way athletes are assessed, and today are routinely used by a number of professional football codes. Near real time systems, have been shown to enable the information to be accessed more quickly and thus the data can be used tactically, for workload management during game play, in addition to post game analysis. On e of the major challenges is to have robust wireless network solutions for this challenging environment. This paper implements a number of player based network topologies and protocols in a simulation environment to test various scenarios, as a tool for future development. Performance limitations to throughput and goodput are used to identify potential bottlenecks. Because the construction of physical hardware devices for athletes and networks, simulation is an attractive process that can shorten development time, identify and solve design problems more rapidly. These tests are intended as an input to designing better devices, networks and thus optimizing ambulatory systems for range, battery life and size reduction.

Performance of the 802.11p Physical Layer in Vehicle-to-Vehicle Environments

A reliable robust wireless network of connected vehicles is desired to enable a number of future telematics and infotainment applications in the vehicular domain. To achieve this objective, vehicle-to-vehicle (V2V) communication is standardized by the IEEE 802.11p Dedicated Short Range Communications (DSRC) standard. Providing reliable communication performance in a highly dynamic time-varying V2V channel is a challenging task. To tackle this challenge, we propose a dynamic equalization scheme, on top of the existing DSRC technology, that significantly improves the packet error rate (PER) of data transmissions without changing the DSRC standard. We also show a hardware implementation of this scheme based on a field-programmable gate array (FPGA) to demonstrate its implementation feasibility. Furthermore, we extend our improved equalization scheme to various data rate options available in the DSRC standard, showing that the proposed scheme is sufficiently generic to support different types of V2V communication. Finally, we report the results of investigating the dependence of wireless communication performance (in terms of PER and throughput) on various design parameters such as packet length, payload size, and data rate.

The Ohio State University College of Medicine

The Ohio State University College of Medicine