MIMO OFDM DOA Estimation Algorithm Implementation and Validation Using SDR Platform

The work is devoted to research in Mobile Station (MS) positioning techniques having opportunity and perspective of using in the next generation communication networks, particularly in cellular networks. Direction of Arrival (DOA) estimation is necessary in many positioning applications and has been well studied by academy and by industry. The main contribution of this work is to design and implement a computationally light direction of arrival estimator on a Multiple Input Multiple Output (MIMO) Software Defined Radio (SDR) platform. Implemented direction of arrival estimator is tested and validated in real conditions and experimental measurements show, that the implemented algorithm can accurately estimate the directions of arrived signals. Used algorithm, estimates direction of arrivals by processing received data of 16-element two dimensional planar antenna array. The algorithm uses initial data received from channel estimators and further process it to obtain direction information. The hardware implementation has been thoroughly analyzed and experimentally validated and open source host code is available on GitHub

MIMO OFDM DOA Estimation Algorithm Implementation and Validation Using SDR Platform

The work is devoted to research in Mobile Station (MS) positioning techniques having opportunity and perspective of using in the next generation communication networks, particularly in cellular networks. Direction of Arrival (DOA) estimation is necessary in many positioning applications and has been well studied by academy and by industry. The main contribution of this work is to design and implement a computationally light direction of arrival estimator on a Multiple Input Multiple Output (MIMO) Software Defined Radio (SDR) platform. Implemented direction of arrival estimator is tested and validated in real conditions and experimental measurements show, that the implemented algorithm can accurately estimate the directions of arrived signals. Used algorithm, estimates direction of arrivals by processing received data of 16-element two dimensional planar antenna array. The algorithm uses initial data received from channel estimators and further process it to obtain direction information. The hardware implementation has been thoroughly analyzed and experimentally validated and open source host code is available on Github

An FPGA implementation of OFDM transceiver for LTE applications

The paper presents a real-time transceiver using an Orthogonal Frequency-Division Multiplexing (OFDM) signaling scheme. The transceiver is implemented on a Field- Programmable Gate Array (FPGA) through Xilinx System Generator for DSP and includes all the blocks needed for the transmission path of OFDM. The transmitter frame can be reconfigured for different pilot and data schemes. In the receiver, time-domain synchronization is achieved thr ough a joint maximum likelihood (ML) symbol arrival-time and carrier frequency offset (CFO) estimator through the redundant information contained in the cyclic prefix (CP). A least-squares channel estimation retrieves the channel state information and a simple zero-forcing scheme has been implemented for channel equalization. Results show that a rough implementation of the signal path can be impleme nted by using only Xilinx System Generator for DSP

Performance of an Echo Canceller and Channel Estimator for On-Channel Repeaters in DVB-T/H Networks

This paper investigates the design and performance of an FIR echo canceller for on-channel repeaters in DVB-T/H network within the framework of the PLUTO project. The possible approaches for echo cancellation are briefly reviewed and the main guidelines for the design of such systems are presented. The main system parameters are discussed. The performance of an FIR echo canceller based on an open loop feedforward approach for channel estimation is tested for different radio channel conditions and for different number of taps of the FIR filter. It is shown that a minimum number of taps is recommended to achieve a certain mean rejection ratio or isolation depending on the type of channel. The expected degradation in performance due to the use of fixed point rather than floating point arithmetic in hardware implementation is presented for different number of bits. Channel estimation based on training sequences is investigated. The performance of Maximum Length Sequences and Constant Amplitude Zero Autocorrelation (CAZAC) Sequences is compared for different channels. Recommendations are given for training sequence type, length and level for DVB-T/H on-channel repeater deployment

Direction of Arrival Estimation for Radio Positioning: a Hardware Implementation Perspective

Nowadays multiple antenna wireless systems have gained considerable attention due to their capability to increase performance. Advances in theory have introduced several new schemes that rely on multiple antennas and aim to increase data rate, diversity gain, or to provide multiuser capabilities, beamforming and direction finding (DF) features. In this respect, it has been shown that a multiple antenna receiver can be potentially used to perform radio localization by using the direction of arrival (DoA) estimation technique. In this field, the literature is extensive and gathers the results of almost four decades of research activities. Among the most cited techniques that have been developed, we find the so called high-resolution algorithms, such as multiple signal classification (MUSIC), or estimation of signal parameters via rotational invariance (ESPRIT). Theoretical analysis as well as simulation results have demonstrated their excellent performance to the point that they are usually considered as reference for the comparison with other algorithms. However, such a performance is not necessarily obtained in a real system due to the presence of non idealities. These can be divided into two categories: the impairments due to the antenna array, and the impairments due to the multiple radio frequency (RF) and acquisition front-ends (FEs). The former are strongly influenced by the manufacturing accuracy and, depending on the required DoA resolution, have to be taken into account. Several works address these issues in the literature. The multiple FE non idealities, instead, are usually not considered in the DoA estimation literature, even if they can have a detrimental effect on the performance. This has motivated the research work in this thesis that addresses the problem of DoA estimation from a practical implementation perspective, emphasizing the impact of the hardware impairments on the final performance. This work is substantiated by measurements done on a state-of-the-art hardware platform that have pointed out the presence of non idealities such as DC offsets, phase noise (PN), carrier frequency offsets (CFOs), and phase offsets (POs) among receivers. Particularly, the hardware platform will be herein described and examined to understand what non idealities can affect the DoA estimation performance. This analysis will bring to identify which features a DF system should have to reach certain performance. Another important issue is the number of antenna elements. In fact, it is usually limited by practical considerations, such as size, costs, and also complexity. However, the most cited DoA estimation algorithms need a high number of antenna elements, and this does not yield them suitable to be implemented in a real system. Motivated by this consideration, the final part of this work will describe a novel DoA estimation algorithm that can be used when multipath propagation occurs. This algorithm does not need a high number of antenna elements to be implemented, and it shows good performance despite its low implementation/computational complexity

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Performance Comparison Between Music And Esprit Algorithms For Direction Estimation Of Arrival Signals

This thesis examines and compares the performance of Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) for the estimation of Direction of Arrival (DOA) of incoming signals to the smart antenna. The comparison of these two algorithms was done on the basis of parameters like number of array elements, number of incoming signals, angle difference between the incoming signals, number of the samples taken of signal, processing time and SNR ratio. These two algorithms were implemented with MATLAB and SIMULINK for the experimental purpose. After all the experiments performed, it was analyzed that results obtained from both of the software were almost same. Comparing MUSIC\u27s results with ESPRIT, it was found that MUSIC is less prone to error than ESPRIT for almost all parametric tests. This superiority of MUSIC made it desirable to recommend it for DOA estimation in smart antenna system

A Hardware Platform for Communication and Localization Performance Evaluation of Devices inside the Human Body

Body area networks (BAN) is a technology gaining widespread attention for application in medical examination, monitoring and emergency therapy. The basic concept of BAN is monitoring a set of sensors on or inside the human body which enable transfer of vital parameters between the patient´s location and the physician in charge. As body area network has certain characteristics, which impose new demands on performance evaluation of systems for wireless access and localization for medical sensors. However, real-time performance evaluation and localization in wireless body area networks is extremely challenging due to the unfeasibility of experimenting with actual devices inside the human body. Thus, we see a need for a real-time hardware platform, and this thesis addressed this need. In this thesis, we introduced a unique hardware platform for performance evaluation of body area wireless access and in-body localization. This hardware platform utilizes a wideband multipath channel simulator, the Elektrobit PROPSimâ„¢ C8, and a typical medical implantable device, the Zarlink ZL70101 Advanced Development Kit. For simulation of BAN channels, we adopt the channel model defined for the Medical Implant Communication Service (MICS) band. Packet Reception Rate (PRR) is analyzed as the criteria to evaluate the performance of wireless access. Several body area propagation scenarios simulated using this hardware platform are validated, compared and analyzed. We show that among three modulations, two forms of 2FSK and 4FSK. The one with lowest raw data rate achieves best PRR, in other word, best wireless access performance. We also show that the channel model inside the human body predicts better wireless access performance than through the human body. For in-body localization, we focus on a Received Signal Strength (RSS) based localization algorithm. An improved maximum likelihood algorithm is introduced and applied. A number of points along the propagation path in the small intestine are studied and compared. Localization error is analyzed for different sensor positions. We also compared our error result with the Cramèr- Rao lower bound (CRLB), shows that our localization algorithm has acceptable performance. We evaluate multiple medical sensors as device under test with our hardware platform, yielding satisfactory localization performance