Performance Analysis and Mitigation Method for I/Q Imbalance-Impaired Time Reversal-Based Indoor Positioning Systems

Time reversal has been shown as a promising technology for the indoor positioning. Instead of mitigating the multipath channel, the time reversal based indoor positioning system (TRIPS) exploits the rich multipath propagation in indoor environments as a specific signature for each location. In order to do this, a database should be first constructed by channel probing. The devices used in this process are assumed to have no hardware impairments or be well calibrated. However, the low cost terminal to be located can exhibit impairments, such as I/Q imbalance at the front end transmitter known to create an interference image of the signal that can particularly impact the performance of time reversal. In this paper, we investigate the impact of the I/Q imbalance on the TRIPS. We analytically show that the I/Q imbalance modifies the metric used for the localization and hence reduces the spatial focusing gain of TRIPS. Numerical simulations are carried out to evaluate this observation. The results further show that the I/Q imbalance creates errors in the positioning estimation. More specifically, at the gain and phase imbalances of respectively 1.1 and 10°, the focusing gain reduction is about 0.5 dB while the estimation error rate is increased by about 5% in the specified scenario.

In recent years, indoor and outdoor positioning technology for the blind has attracted much more attention. The outdoor positioning technology has relatively matured. However, three-dimensional indoor positioning technology is facing many problems. Due to low positioning accuracy as well as slow positioning speed, there is no ideal implementation system at present. Light Fidelity (LiFi) technology is a new wireless transmission technology that uses the visible light spectrum, such as the light emitted by a light bulb, to transmit data. It transmits signals through the changing light of LED lights. When LED lights are properly laid out in the building, not only the function of lighting but also that of transmitting information are met at the same time. It is a good way to solve indoor positioning problems. This article studies an indoor positioning glasses for blind based on the LiFi technology. Different from other indoor positioning technologies such as ultrasound and wireless fidelity (WiFi), the design of indoor positioning glasses for the blind will propose new ideas of three-dimensional indoor positioning problems for the blind.

Understanding the indoor whereabouts of individuals and objects is important, especially for those who fall within the 71% of visually impaired individuals with a school education, students in 450 special education units and many other areas and aspects in Sri Lanka. Researchers have declared that, there isn’t any particularly good localization system, and the performance should be evaluated considering the approach and application. The most well-known indoor positioning (IP) technologies that have been historically deployed are Bluetooth, Wi-Fi, RFID (radio frequency identification), IR (Infrared), and UV (ultraviolet) whereas received signal strength (RSSI), fingerprinting, and triangulation methods have been used as common IP techniques. The combination of both IP technologies and techniques creates an IP system, and the integration of machine learning and IoT with the structured system essentially delivers an accurate and more advanced system. This paper contains a detailed, analytical review of a developed indoor positioning system derived from the existing indoor localization techniques, localization technologies, localization systems, algorithms, and performance matrixes. This also provides a comprehensive comparison between numerous existing systems to justify the proposed solution. This project has been developed to achieve better accuracy through low-cost deployment as an effective system to fill the gap in the scarcity of positioning systems in the world. This paper presents a descriptive introduction and problem definition, a critical discussion of results, machine learning models, benefits of the project, and future works. As later justified, ESP32 microcontroller and BLE beacons are utilized with RSSI fingerprinting method to develop this IP system and, as a part of the project, two data visualization methods have been introduced here using NodeRED dashboard and LC display. Overall, this project was developed with an effective combination of RSSI fingerprinting, IoT protocols, machine learning, and data interpretation methods. KEYWORDS: Indoor positioning, RSSI, Fingerprinting, Machine Learning, MQTT, ESP32, BLE beacons, NodeRED

This study investigates the performance of Dual-mode index modulation aided orthogonal frequency division multiplexing (DM-OFDM) systems under hardware impairments and varying channel conditions. The spectral efficiency provided by dual-mode operation is analyzed in comparison to conventional index modulation OFDM (OFDM-IM) over Rayleigh and Rician fading channels. Practical hardware impairments, such as phase noise and IQ imbalance, are incorporated into the model to evaluate their effects. Simulations conducted for different subcarrier numbers (N=64/128/256) and active subcarrier configurations (K=1/2/3) demonstrate that DM-OFDM outperforms conventional OFDM-IM in terms of bit error rate (BER) performance under both channel conditions. In high signal to noise ratio (SNR) regions, an error floor caused by hardware distortions is observed, emphasizing the need to consider this effect in system design. While increasing the number of subcarriers and optimizing active subcarrier selection enhances performance, the line-of-sight component in the Rician channel further improves the system's performance.

Wireless signal propagation in indoor environments is generally affected by various factors such as multi-path fading, temperature and humidity. It is thus challenging to use the simple metric of Received Signal Strength (RSS) for indoor localization. Prior work often requires manual profiling of each indoor environment to achieve good accuracy. We, instead, propose a simple generic localization algorithm that can be applied in any indoor environment without profiling. Our algorithm makes use of a simple signal propagation model and accepts a broad characterization of the environmental effect. The algorithm's simplification results in some accuracy loss compared to profiling-based algorithms. We, however, believe that our algorithm's zero-profiling requirement would make it favorable in many scenarios, especially when extensive profiling is not affordable or it is favored to trade a little accuracy for saved human effort. Evaluations also show that deployment of additional landmarks can be combined with our algorithm to compensate the accuracy loss, thus achieving good accuracy without profiling.

A multipath model of UWB pulse propagation in the indoor environment is addressed in this paper. The simulation utilizes the principles of geometrical optics (GO) for direct and reflected paths' tracing and time domain technique for describing the transient electromagnetic field reflected from wall, floor, ceiling, and objects. The closed-form time domain analytic solution for UWB impulse signal reflection, which takes into account the frequency range from 3. 1 to 10.6 GHz, is proposed, and it is suitable for dry concrete, wood, glass, etc. , which are envisioned as common building construction materials for indoor environment. A specific house with two cube-like objects, which is thought to be a more realistic environment, is investigated. The simulation results provide the three-dimension (3D) space-time distribution of received pulsed field, which give more intrinsically interpretations for the mechanics of UWB impulse signals propagation in indoor environment.

Future communication system requires large bandwidths to achieve high data rates, thus rendering analog-to-digital conversion (ADC) a bottleneck due to its high power consumption. In this paper, we consider monobit receivers for QPSK. The optimal monobit receiver under Nyquist sampling is obtained and its performance is analyzed. Then, a suboptimal but low-complexity receiver is proposed. The effect of imbalances between In-phase (I) and Quadrature (Q) branches is carefully examined. To combat the performance loss due to IQ imbalances, monobit receivers based on double training sequences and eight-sector phase quantization are proposed. Numerical simulations show that the low-complexity suboptimal receiver suffers 3dB signal-to-noise-ratio (SNR) loss in additive white Gaussian noise (AWGN) channels and only 1dB SNR loss in multipath channels compared with matched-filter monobit receiver with perfect channel state information (CSI). It is further demonstrated that the amplitude imbalance has essentially no effect on monobit receivers. In AWGN channels, receivers based on double training sequences can efficiently compensate for the SNR loss without complexity increase, while receivers with eight-sector phase quantization can almost completely eliminate the SNR loss caused by IQ imbalances. In dense multipath channels, the effect of imbalances on monobit receivers is slight.

High-precision indoor positioning technology is regarded as one of the core components of artificial intelligence (AI) and Internet of Things (IoT) applications. Over the past decades, society has observed a burgeoning demand for indoor location-based services (iLBSs). Concurrently, ongoing technological innovations have been instrumental in establishing more accurate, particularly meter-level indoor positioning systems. In scenarios where the penetration of satellite signals indoors proves problematic, research efforts focused on high-precision intelligent indoor positioning technology have seen a substantial increase. Consequently, a stable assortment of location sources and their respective positioning methods have emerged, characterizing modern technological resilience. This academic composition serves to illuminate the current status of meter-level indoor positioning technologies. An in-depth overview is provided in this paper, segmenting these technologies into distinct types based on specific positioning principles such as geometric relationships, fingerprint matching, incremental estimation, and quantum navigation. The purpose and principles underlying each method are elucidated, followed by a rigorous examination and analysis of their respective technological strides. Subsequently, we encapsulate the unique attributes and strengths of high-precision indoor positioning technology in a concise summary. This thorough investigation aspires to be a catalyst in the progression and refinement of indoor positioning technologies. Lastly, we broach prospective trends, including diversification, intelligence, and popularization, and we speculate on a bright future ripe with opportunities for these technological innovations.

In recent years, with the development of situational awareness and the application of environmental intelligence, the requirements for user location positioning are becoming more and more accurate. At present, the indoor positioning technology is still in the R&D stage relatively. This paper analyzes the current status of indoor location and various positioning technologies, discusses the characteristics and advantages and disadvantages of different location methods, the problems faced to indoor positioning. Finally, it briefly introduces the future research direction and development trend in this field.

According to the paper published at 2010-2013 Indoor Positioning and Indoor Navigation (IPIN), this paper classify the indoor position technology to four classes by technical characteristics. The developing trends and main characteristics of future indoor position technology are deduced based on the paper data published by IPIN. The bottlenecks of indoor position technology was proposed. Finally, the future development trend of indoor position technology was predicted.

At present, location technology divides into outdoor location technology and indoor location technology. Comparing with other indoor location methods, ultra-wide band (UWB)indoor location technology has the advantages of strong anti-multipath interference ability and signal penetration ability. But, when this method faces large obstacles or metal obstacles, non line of sight (NLOS) will still occur. Indoor location system is a part of our project Home Care System for The Elderly. The NLOS of Indoor location system reduces the reliability of Home Care System for The Elderly. In order to improve the accuracy of location and efficiency of operation, an NLOS detection method based on k-nearest neighbors (KNN) algorithm is proposed. This algorithm modeled the training samples to find the K value with the highest recognition accuracy. The experimental results show that The NLOS detection accuracy of this method is 78% in the simulated apartment scene. With the same number of samples, the accuracy of the widely used Convolutional Neural Networks (CNN) algorithm is 67%. The experimental results show that KNN algorithm is more suitable for Home Care System for The Elderly for it can keep high accuracy with less requirement for the number of samples than CNN.

Objectives: The growing demand of Wireless connectivity supported in the 802.11 standard has caused a high demand of wireless networks by the users, due to the benefits of mobility and low-cost implementation. Such networks have been used in common places such as houses, offices, schools among others. The objective of this article is to propose an empiric propagation model, supported in the Log-Normal-Shadowing Path Loss model for 2.4 GHz and 5 GHz bands in Indoor environments, compatible with University campus building. Methods/Statistical Analysis: A scenario of a six-storey building on a university campus was proposed, with dimensions of 60 m long, 34 m wide and 24 m high. Additionally, such building has 24 Access Points (AP) distributed in such a way that allow network to serve connectivity to its students. In order to establish the expressions that describe the Log-Normal-Shadowing Path Loss propagation model, an experimental design of factorial mixed type was considered involving three factors: frequency band (2.4 GHz or 5 GHz), condition of the media (Free space or with obstacles) and the distance between the receiver and the AP. The experiment aims to assess how each factor influences on the Received Signal Strength Indicator RSSI. Topic Significance: The proposed model will be used to run analysis of radio propagation in indoor environments using institutional educational buildings and holding a capacity of carrying out prediction processes of RSSI, in the 2.4 GHz and 5 GHz bands. Findings: Based on obtained results, it was possible to evidence that the established models allow predicting the behavior the reception power and signal damping, with a level of confidence of 95%. Additionally, it was possible to verify, in the 5 GHZ band, the damping levels are bigger that those in 2.4 GHz band. Such aspect holds great importance when it comes to perform design processes of Wireless networks. Applications/Improvements: In future research papers, it would be significantly important to establish the expression for outdoor environments, supported in the Shadowing Path model. Keywords: Channels Allocation, Efficiency, Optimization, Performance, SINR, WLAN

Cross-polarization discrimination of MIMO antenna configuration at a mobile station in indoor propagation environment

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this special issue present recent advances and new developments in indoor localization systems and technologies, proposing novel or improved methods with increased performance, providing insight into various aspects of quality control, and also introducing some unorthodox positioning methods.

We propose a novel training symbol structure for polarization division multiplexed (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. We deduce the mathematical model for the scheme. Based on the given model, a novel compensation method is introduced to compensate the IQ imbalance. The theoretical analysis is validated by numerical simulation, in which we apply the Quadrature Phase Shift Keying (QPSK) modulation at a data rate of 75.211Gb/s over 50 km and data rate of 100Gb/s over 320 km transmission. Compared with the commonly used approach, the proposed scheme demonstrates better system BER performance against IQ imbalance.