Maximum Received Signal Strength Research Articles

Optimization of received signal strength in visible light communication using the combination of heuristic algorithms

SummaryLEDs are a prominent technique for a pervasive communication system using visible light communication (VLC), since LED includes long life expectancy, fast switching, and being visible light and is less expensive, which is safe for the human body, though still many technical problems presented to be addressed, especially in an indoor environment. Due to this, the major aim of this task is to afford a hybridized optimization algorithm that is highly suitable for enabling the signal to noise ratio (SNR) and received signal strength (RSS) maximization in VLC. Here, the coordinate of each point of the receiver photo detector in the VLC system is tuned by the new hybridized algorithm. The fusion of two optimization algorithms like Deer Hunting Optimization Algorithm (DHOA) and Dragonfly Algorithm (DA) termed as Fitness‐oriented Dragonfly‐based DHOA (FD‐DHOA) is used to attain the objective concerning the RSS or received power and SNR. The proposed model tries to attain maximum RSS and SNR at the receiver instead of calculating it at every angle. Moreover, the experimental analysis proves that the developed model validates the orientation that generates an optimum RSS and SNR value at the receiver.

Bio-inspired algorithm for decisioning wireless access point installation

<p class="p1"><span lang="EN-US">This paper presents the bio-inspired algorithms for decisioning wireless access point (AP) installation. In order to achieve the desired coverage capability of APs, the bio-inspired algorithms are applied for robust competition and optimization. The main objective is to determine the optimal number of APs with the high coverage capability in the concerning area using the genetic and ant colony optimization algorithms. Received signal strength indicator (RSSI) and line-of-sight (LoS) gradient approach are the most important parameters for AP installation depending on the AP signal strength. Practical experiments are tested on the embedded system using Xilinx Kria KR260 and Raspberry Pi Zero 2W boards at the tested room size about 16 m wide and 40 m long inside the building. Xilinx Kria KR260 board is used to calculate the number of AP installation and localization compared to Xcode. Then, Raspberry Pi Zero 2W board is the representation of wireless AP for measuring the signal in the testing area. Experiment results show that maximum received signals strength is equal to -35 dBm at 6 m and there are six APs installation with high coverage area and maximum received signal strength at the area of 16×40 m<sup>2</sup>.</span></p>

A Two-Nearest Wireless Access Point-Based Fingerprint Clustering Algorithm for Improved Indoor Wireless Localization

Fingerprint database clustering is one of the methods used to reduce localization time and improve localization accuracy in a fingerprint-based localization system. However, optimal selection of initial hyperparameters, higher computation complexity, and interpretation difficulty are among the performance-limiting factors of these clustering algorithms. This paper aims to improve localization time and accuracy by proposing a clustering algorithm that is extremely efficient and accurate at clustering fingerprint databases without requiring the selection of optimal initial hyperparameters, is computationally light, and is easily interpreted. The two closest wireless access points (APs) to the reference location where the fingerprint is generated, as well as the labels of the two APs in vector form, are used by the proposed algorithm to cluster fingerprints. The simulation result shows that the proposed clustering algorithm has a localization time that is at least 45% faster and a localization accuracy that is at least 25% higher than the k-means, fuzzy c-means, and lightweight maximum received signal strength clustering algorithms. The findings of this paper further demonstrate the real-time applicability of the proposed clustering algorithm in the context of indoor wireless localization, as low localization time and higher localization accuracy are the main objectives of any localization system. Doi: 10.28991/ESJ-2023-07-05-019 Full Text: PDF

LoRa and Rotating Polarization Wave: Physical Layer Principles and Performance Evaluation

Link reliability and enhanced coverage are the primitive concerns of Low-Power Wide-Area Networks (LPWANs) for suitability to critical Internet of Things (IoT) applications. Reliability is limited by the destructive multipath propagation, data rate and sensitivity, that ultimately limits the coverage range. LoRa by far is the predominant LPWAN operating on unlicensed spectrum. Despite its robust Chirp Spread Spectrum (CSS) modulation, there is a severe degradation in its error performance particularly in hostile propagation environments, and an excessive reduction in coverage. Rotating Polarization Wave (RPW) is a potential LPWAN recently emerged to achieve a highly reliable IoT and Machine-to-Machine (M2M) communication. This is the first paper to provide comprehensive error performance comparison between LoRa and RPW. Okumura-Hata model is used for median path loss calculation. Shadowing and fast fading margins of RPW and LoRa are estimated. Effective gain of RPW is computed from error performance. Results have shown that LoRa offers a sensitivity of 23 dB higher than RPW under AWGN conditions. However, under fading conditions, RPW exhibits a sensitivity of 15 dB higher than LoRa. At a reference distance of 100 m, the maximum received signal strength of RPW is -39 dBm, which is 29 dB above LoRa. The maximum coverage distance attained by RPW is 15 km, which is 1.5 times of LoRa.

A Novel Optimized V-VLC Receiver Sensor Design Using μGA in Automotive Applications.

Vehicular visible light communication is known as a promising way of inter-vehicle communication. Vehicular VLC can ensure the significant advancement of safety and efficiency in traffic. It has disadvantages, such as unexpected glare on drivers in moving conditions, i.e., non-line-of-sight link at night. While designing a receiver, the most important factor is to ensure the optimal quality of the received signal. Within this context, to achieve an optimal communication quality, it is necessary to find the optimal maximum signal strength. Hereafter, a new receiver design is focused on in this paper at the circuit level, and a novel micro genetic algorithm is proposed to optimize the signal strength. The receiver can calculate the SNR, and it is possible to modify its structural design. The micro GA determines the alignment of the maximum signal strength at the receiver point rather than monitoring the signal strength for each angle. The results showed that the proposed scheme accurately estimates the alignment of the receiver, which gives the optimum signal strength. In comparison with the conventional GA, the micro GA results showed that the maximum received signal strength was improved by −1.7 dBm, −2.6 dBm for user Location 1 and user Location 2, respectively, which proves that the micro GA is more efficient. The execution time of the conventional GA was 7.1 s, while the micro GA showed 0.7 s. Furthermore, at a low SNR, the receiver showed robust communication for automotive applications.

Clustering-based adaptive low-power subframe configuration with load-aware offsetting in dense heterogeneous networks

Heterogeneous Networks (HetNets) and cell densification represent promising solutions for the surging data traffic demand in wireless networks. In dense HetNets, user traffic is steered toward the Low-Power Node (LPN) when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency. However, because of the transmit power differences in different tiers of HetNets and irregular service demand, a load imbalance typically exists among different serving nodes. To offload more traffic to LPNs and coordinate the Inter-Cell Interference (ICI), Third-Generation Partnership Project (3GPP) has facilitated the development of the Cell Range Expansion (CRE), enhanced Inter-Cell Interference Coordination (eICIC) and Further enhanced ICIC (FeICIC). In this paper, we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe (LPS) approach. Our solution allows the separation of User Association (UA) functions at the User Equipment (UE) and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength (max-RSS) based UA scheme, where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system. The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions. Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.

User association for load balancing in coordinated multipoint green HetNets: A Quasi-Newton-based approach

The demand for high capacity network services with stringent quality of service requirements is at a rapidly accelerating rate due to the exponential rise in the numbers of mobile-connected devices. This demand has motivated the use of the heterogeneous network (HetNet) architectures. However, even though small-cell base-stations have relatively low power consumption, the overall aggregate power consumption of a dense HetNet is significant. Due to high inter-cell-interference and imbalanced loads in dense HetNets with conventional user association techniques, cell-edge users perceive dramatically less quality of service than their cell-center counterparts. The use of a Coordinated Multipoint (CoMP) association can augment the service perceived by cell-edge users by allowing a single user to be jointly served by two base-stations. In this work, we propose a load balancing scheme for CoMP-enabled HetNets with hybrid energy supplies that jointly optimizes user latency and green energy utilization. The proposed scheme employs a fractional solution to the user association problem to decide CoMP transmission for cell-edge users, ultimately improving their data rates. Performance evaluations of the proposed scheme show a reduction in latency of 79% and on-grid power consumption by 99% compared to conventional user association schemes that associate users based on the maximum received signal strength. Furthermore, an improvement in the network sum-rate for cell-edge users by 24% has been achieved compared to the traditional association scheme and as much as 40% over other existing schemes.

Radar Position Estimation by Sequential Irradiation of ESM Receivers.

In this article, a new technique for determination of 2D signal source (target) position is proposed. This novel approach, called the Inscribed Angle (InA), is based on measuring the time difference of sequential irradiation by the main beam of the target antenna’s radiation pattern, using Electronic Support Measures (ESM) receivers, assuming that the target antenna is rotating and that its angular velocity is constant. In addition, it is also assumed that the localization system operates in a LOS (Line of Sight) situation and that three time-synchronized sensors are placed arbitrarily across the area. The main contribution of the article is a complete description of the proposed localization method. That is, this paper demonstrates a geometric representation and an InA localization technique model. Analysis of the method’s accuracy is also demonstrated. The time of irradiation of the receiving station corresponds to the direction in which the maximum received signal strength (RSS) was measured. In order to achieve a certain degree of accuracy of the proposed positioning technique, a method was derived to increase the accuracy of the irradiation time estimation. Finally, extensive simulation was conducted to demonstrate the performance and accuracy of our positioning method.

BS-UE Association and Power Allocation in Heterogeneous Massive MIMO Systems

We consider a downlink Heterogeneous Massive Multiple-Input Multiple-Output (HM-MIMO) system with the macro-base station (BS) having hundreds of antennas and each of the micro-BSs having tens of antennas. Two lower bounds and one approximation of the achievable per-user equipment (UE) rate in closed forms under this system are derived and compared in terms of network utility. Using the derived approximation, three BS-UE association approaches are proposed. Firstly, a simple, sub-optimal, and heuristic multiple BS-UE association approach is designed, which achieves around 25% utility performance improvement compared with the conventional maximum received signal strength (Max-RSS) approach. Secondly, based on the results given by this heuristic approach, a learning approach for BS-UE association using convolutional neural network (CNN) is introduced. After being fully trained, the CNN can take any new BS-UE configuration as input and provide a sub-optimal BS-UE association for that configuration directly. It has only a small performance degradation compared with the proposed heuristic approach. Thirdly, realizing that the BS-UE connection probability in the proposed CNN architecture can be considered as a power allocation ratio, a combined power allocation and association approach is proposed. Its performance achieves as high as 60% utility improvement compared with the Max-RSS association and is also comparable to that achieved by the max-min power allocation approach which requires more than $10000\times $ running time. It is remarkable that by using the gradients of the derived achievable per-UE rate approximation with respect to the power control coefficients, accurate target data is in fact not required for training in this approach.

Interference Management in In-Band D2D Underlaid Cellular Networks

Recently, it has been standardized by the 3rd generation partnership project (3GPP) that device-to-device (D2D) communications should use uplink resources when coexisting with conventional cellular communications. With uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we address the critical issue of interference management in the network considering a practical path loss model incorporating both line-of-sight (LoS) and non-LoS (NLoS) transmissions. To reduce the severe interference caused by active D2D links, we consider a mode selection scheme based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Furthermore, we analyze the performance in terms of the coverage probability and the area spectral efficiency (ASE) for both the cellular network and the D2D one. Analytical results are obtained and the accuracy of the proposed analytical framework is validated through Monte Carlo simulations. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications in cellular networks and we find an optimum mode selection threshold $\beta $ to maximize the total ASE in the network. This insight is expected to provide a design guideline for D2D mode selections.

Energy efficient SBSs sleep mode analysis for successive user association and resource scheduling algorithms in two‐tier heterogeneous network

This study analyses and compares the downlink energy efficiency (EE) of user association and resource scheduling algorithms considering sleep mode of small cell base stations (SBSs) in two-tier heterogeneous cellular networks. Owing to the NP-hardness of joint user association and resource scheduling algorithms, the authors successively perform user association and resource scheduling algorithms. Firstly, in the user association algorithms, sleep mode for the SBSs without associated users is considered to improve EE, where they associate users with the macrocell base station (MBS) or SBSs according to three signal strength strategies, namely, unbiased user association, biased user association and signal to interference plus noise ratio-based user association. Then, in the resource scheduling algorithms, they schedule the MBS and SBSs resource blocks to users based on three scheduling criteria, i.e. maximum received signal strength, round robin and proportional fairness, respectively. Fairness among users is also analysed. In the simulation, numerical results for different successive user association and resource scheduling algorithms are compared. The optimum algorithms are found in the different network environments. These results are significant for the heterogeneous network operation to get high EE.

Analysis of Underlaid D2D-Enhanced Cellular Networks: Interference Management and Proportional Fair Scheduler

Device-to-device (D2D) communications have been proposed as a promising technology to improve network capacity and user experiences in the future mobile networks such as heterogeneous networks with densely deployed small cells, but it has not yet been fully incorporated into the existing cellular networks. Interference management is one of the critical issues when D2D communications using uplink resources and coexisting with conventional cellular communications, especially in the ultra-dense networks (UNDs). In this paper, we address the critical issue of interference management by a mode selection method, which is based on the maximum received signal strength (MRSS) for each D2D transmitter (TU). To analyze the capacity of a more practical D2D-enhanced network, we consider that the typical user is no longer a random user, i.e., random user selection by a round-robin (RR) scheduler, as assumed in most studies in the literature. Instead, a cellular user with the maximum proportional fair (PF) metric is chosen by its serving base station as the typical user, which is referred to as the PF scheduler in the cellular tier. Furthermore, we theoretically study the performance in terms of the coverage probability and the area spectral efficiency (ASE) for both the cellular network and the D2D one with the consideration of the PF scheduler in UDNs. Analytical results are obtained, and the accuracy of the proposed analytical framework is validated through Monte Carlo simulations. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and the PF scheduler in cellular networks, and we find an optimum mode selection threshold $\beta $ to maximize the total ASE in the network.

Robust Localization for Cognitive IoT via the Mobile Anchor Node Based on the Diameter-Varying Spiral Line

Research on IoT that merely aims at connecting and communicating is about to past. Thereafter, general objects should have the capability to learn, think, and understand both physical and social areas by themselves. Cognitive Internet of Things (CIoT) attempts to empower the current IoT with a “brain” for high-level intelligence, requiring networks to have the ability to bridge the physical and social worlds. This attempt means matching equipment and resources with people and their behavior. Therefore, accurate location information is crucial for equipment connecting to CIoT. This endeavor sets a higher requirement for the localization technology of wireless sensor networks in terms of accuracy, energy, and efficiency compared with that in the past. In this paper, we propose an efficient and accurate mobile anchor node assisted localization algorithm for WSNs based on diameter-varying spiral line (LDVSL), which broadcasts coordinates of the anchor node to assist localizing unknown sensor nodes. The proposed algorithm has two main innovations. First, we obtain the mobile anchor node position through a time and angle mechanism instead of GPS, given the unique characteristics of the diameter-varying spiral line. Second, the linear fitting method is adapted to select the key virtual node, which has the real maximum received signal strength indicator. Simulations indicate that the proposed LDVSL algorithm outperforms other similar algorithms in terms of average localization error and positionable node ratio. The simulations also show that the LDVSL is not affected by obstacles seriously and has good robustness. The LDVSL has a wide prospect of application in CIoT.

Omnidirectional Radio Propagation Antenna Using Organized Grouping of Monopole Antennas

An omnidirectional radio propagation antenna is designed in the present study by grouping three microstrip monopole antennas of MRF24J40MA transceiver on a transmitter device. MRF24J40MA transceiver is operating at 2.4 GHz of frequency with maximum transmission power of 0 dBm and receiving sensitivity of − 91 dBm. The proposed antenna radiating characteristic is tested by measuring the maximum received signal strength indicator along the angular direction from 0 to 360 degree. The main objective of this letter is to authenticate the work of various localization algorithms based on oversimplification of radio propagation model.

Visible light signal strength optimization using genetic algorithm in non-line-of-sight optical wireless communication

Visible light communication (VLC) using the light emitting diode (LED) attracts attention from researchers as a future low power optical wireless communication. VLC generally considers a line-of-sight (LOS) link, although the LOS link can be affected by the obstacles between LED transmitter and photodetector (PD) receiver in a practical scenario. In the case of non-line-of-sight (NLOS) link, it is important to find a link with maximum possible received signal strength (RSS) to ensure optimum communication quality in VLC. In this paper, we propose a novel scheme for optimizing the RSS using a meta-heuristic searching algorithm known as genetic algorithm (GA). The proposed scheme is simulated using two white light emitting diodes (LEDs) as the transmitters and a PD as the receiver. The genetic algorithm (GA) is used to calculate the maximum RSS on the NLOS link within an indoor environment. GA determines an orientation of the maximum RSS at the receiver instead of measuring the RSS for every angle. Simulation results reveal that the proposed scheme accurately estimates the orientation that produces an optimum RSS value at the receiver.

Regression Based Mobility Estimation Method Using Received Signal Strength

In this paper, estimation of mobility using received signal strength (RSS) is presented. In contrast to standard methods, speed can be estimated without the use of any additional hardware like accelerometer, gyroscope or position estimator. The pattern of mobility can be inferred using any hand-held device such as mobile phone, tablet or smart watch and source of RSS. The strength of Wireless Fidelity (WiFi) signal is considered herein to compute the time-domain features such as mean, minimum, maximum, and autocorrelation of signal strength. The experiments are carried out in different environments like academic area, residential area and in open space. The experimental results indicate that the average accuracy in the estimated speed is 88% using the maximum RSS model with limited data set. The accuracy can be further increased by carrying out the training with a larger dataset. The proposed method is cost-effective and having linear complexity with reasonable accuracy. Additionally, the proposed method is scalable that is the performance is not affected in a multi-smartphones scenario in a WiFi or cellular environment.

A Server-based Flow Allocation Scheme for Streaming Services in Data Center Networks

Abstract Streaming services provided by data centers (DCs) have become increasingly popular. The quality of streaming services greatly depends on network conditions, though, such as available bandwidth and delay time characteristics. To realize high quality stream- ing services, selecting an appropriate access network among available ones is necessary. However, in wireless LANs, a station (STA) simply selects an access point (AP) with the maximum received signal strength to connect to the Internet. Therefore, the service quality will deteriorate when access from STAs is concentrated in a specific AP. In this paper, we propose a server-based flow allocation scheme based on collectable information in DC networks to enable high quality streaming services. This scheme collects information, including the packet loss rate of existing flows as well as the available bandwidth of access networks, and then allocates a streaming flow to an appropriate access network based on the collected information. We show the effectiveness of this approach through simulation evaluations.

REAL TIME RSS BASED ADAPTIVE BEAM STEERING ALGORITHM FOR AUTONOMOUS VEHICLES

A real time, low complexity algorithm is developed to steer a planar patch antenna array beam to the maximum received signal strength (RSS) direction for communication link enhancement. The beam steering towards the maximum incoming signal direction is based on an iterative technique utilizing a set of RSS measurements taken from speciflc locations in the search space, these locations collectively form an ellipse. The algorithm is denoted as \elliptical peeking. It was simulated for a ∞ying unmanned aerial vehicle (UAV) as the vehicle tries to identify the maximum signal strength incoming direction of a stationary ground signal and it was tested on an embedded platform to validate its low demand for computational power. Such an algorithm is suitable for autonomous platforms due to its simplicity and low cost.

Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem

The Wi-Fi fingerprinting (WF) technique normally suffers from the Received Signal Strength (RSS) variance problem caused by environmental changes that are inherent in both the training and localization phases. Several calibration algorithms have been proposed but they only focus on the hardware variance problem. Moreover, smartphones were not evaluated and these are now widely used in WF systems. In this paper, we analyzed various aspects of the RSS variance problem when using smartphones for WF: device type, device placement, user direction, and environmental changes over time. To overcome the RSS variance problem, we also propose a smartphone-based, indoor pedestrian-tracking system. The scheme uses the location where the maximum RSS is observed, which is preserved even though RSS varies significantly. We experimentally validate that the proposed system is tolerant to the RSS variance problem.

Smart Association Control in Wireless Mobile Environment Using Max-Flow

WiFi clients must associate to a specific Access Point (AP) to communicate over the Internet. Current association methods are based on maximum Received Signal Strength Index (RSSI) implying that a client associates to the strongest AP around it. This is a simple scheme that has performed well in purely distributed settings. Modern wireless networks, however, are increasingly being connected by a wired backbone. The backbone allows for out-of-band communication among APs, opening up opportunities for improved protocol design. This paper takes advantage of this opportunity through a coordinated client association scheme where APs consider a global view of the network, and decide on the optimal client-AP association. We show that such an association outperforms RSSI based schemes in several scenarios, while remaining practical and scalable for wide-scale deployment. We also show that optimal association is a NP-Hard problem and our max-flow based heuristic is a promising solution.