Communication and Jamming BDA of OFDMA communication systems using the software defined radio platform WARP

The aim of this research is to demonstrate and evaluate the ability to eavesdrop and interfere with orthogonal frequency division multiple access-down link (OFDMA-DL) signal features utilising Wireless Open Access Research Platform (WARP) boards. The OFDMA-DL waveforms have been developed with 64 sub carriers and have guards and pilots as comparable to the 802.11a WiFi standard. An eavesdropper/interferer (ExJx) is used to estimate signal features, remotely gaining intelligence without alerting the communication system. This research also demonstrates how estimated signal features can be used to interfere with an established communication system. Methods used to perform the signal feature estimation exploit the cyclostationary nature of the OFDMA-DL waveform, with higher order cumulants utilised to classify modulation schemes. To assess the ability of the ExJx system to eavesdrop (Ex), Communication Battle Damage Assessment (CBDA) techniques are used. To assess the ability of the ExJx system to interfere (Jx), Jamming Battle Damage Assessment (JBDA) techniques are used

A case for adaptive sub-carrier level power allocation in OFDMA networks

In today's OFDMA networks, the transmission power is typically fixed and the same for all the sub-carriers that compose a channel. The sub-carriers though, experience different degrees of fading and thus, the received power is different for different sub-carriers; while some frequencies experience deep fades, others are relatively unaffected. In this paper, we make a case of redistributing the power across the sub-carriers (subject to a fixed power budget constraint) to better cope with this frequency selectivity. Specifically, we design a joint power and rate adaptation scheme (called JPRA for short) wherein power redistribution is combined with sub-carrier level rate adaptation to yield significant throughput benefits. We further consider two variants of JPRA: (a) JPRA-CR where, the power is redistributed across sub-carriers so as to support a maximum common rate (CR) across sub-carriers and (b) JPRA-MT where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first variant decreases transceiver complexity and is simpler, the second is geared towards achieving the maximum throughput possible. We implement both variants of JPRA on our WARP radio testbed. Our extensive experiments demonstrate that our scheme provides a 35% improvement in total network throughput in testbed experiments compared to FARA, a scheme where only sub-carrier level rate adaptation is used. We also perform simulations to demonstrate the efficacy of JPRA in larger scale networks. © 2012 ACM

Blind Demodulation of Pass Band OFDMA Signals and Jamming Battle Damage Assessment Utilizing Link Adaptation

This research focuses on blind demodulation of a pass band OFDMA signal so that jamming effectiveness can be assessed; referred to in this research as BDA. The research extends, modifies and collates work within literature to perform a new method of blindly demodulating of a passband OFDMA signal, which exhibits properties of the 802.16 Wireless MAN OFDMA standard, and presents a novel method for performing BDA via observation of SC LA. Blind demodulation is achieved by estimating the carrier frequency, sampling rate, pulse shaping filter roll off factor, synchronization parameters and CFO. The blind demodulator\u27s performance in AWGN and a perfect channel is evaluated where it improves using a greater number OFDMA DL symbols and increased CP length. Performance in a channel with a single multi-path interferer is also evaluated where the blind demodulator\u27s performance is degraded. BDA is achieved via observing SC LA modulation behavior of the blindly demodulated signal between successive OFDMA DL sub frames in two scenarios. The first is where modulation signaling can be used to observe change of SC modulation. The second assumes modulation signaling is not available and the SC\u27s modulation must be classified. Classification of SC modulation is performed using sixth-order cumulants where performance increases with the number of OFDMA symbols. The SC modulation classi er is susceptible to the CFO caused by blind demodulation. In a perfect channel it is shown that SC modulation can be classified using a variety of OFDMA DL sub frame lengths in symbols. The SC modulation classifier experienced degraded performance in a multi-path channel and it is recommended that it is extended to perform channel equalization in future work

Multi-stage Wireless Signal Identification for Blind Interception Receiver Design

Protection of critical wireless infrastructure from malicious attacks has become increasingly important in recent years, with the widespread deployment of various wireless technologies and dramatic growth in user populations. This brings substantial technical challenges to the interception receiver design to sense and identify various wireless signals using different transmission technologies. The key requirements for the receiver design include estimation of the signal parameters/features and classification of the modulation scheme. With the proper identification results, corresponding signal interception techniques can be developed, which can be further employed to enhance the network behaviour analysis and intrusion detection. In detail, the initial stage of the blind interception receiver design is to identify the signal parameters. In the thesis, two low-complexity approaches are provided to realize the parameter estimation, which are based on iterative cyclostationary analysis and envelope spectrum estimation, respectively. With the estimated signal parameters, automatic modulation classification (AMC) is performed to automatically identify the modulation schemes of the transmitted signals. A novel approach is presented based on Gaussian Mixture Models (GMM) in Chapter 4. The approach is capable of mitigating the negative effect from multipath fading channel. To validate the proposed design, the performance is evaluated under an experimental propagation environment. The results show that the proposed design is capable of adapting blind parameter estimation, realize timing and frequency synchronization and classifying the modulation schemes with improved performances

A Summative Comparison of Blind Channel Estimation Techniques for Orthogonal Frequency Division Multiplexing Systems

The OFDM techniquei.e. Orthogonal frequency division multiplexing has become prominent in wireless communication since its instruction in 1950’s due to its feature of combating the multipath fading and other losses. In an OFDM system, a large number of orthogonal, overlapping, narrow band subchannels or subcarriers, transmitted in parallel, divide the available transmission bandwidth. The separation of the subcarriers is theoretically optimal such that there is a very compact spectral utilization. This paper reviewed the possible approaches for blind channel estimation in the light of the improved performance in terms of speed of convergence and complexity. There were various researches which adopted the ways for channel estimation for Blind, Semi Blind and trained channel estimators and detectors. Various ways of channel estimation such as Subspace, iteration based, LMSE or MSE based (using statistical methods), SDR, Maximum likelihood approach, cyclostationarity, Redundancy and Cyclic prefix based. The paper reviewed all the above approaches in order to summarize the outcomes of approaches aimed at optimum performance for channel estimation in OFDM system

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed