Most of the MIMO-OFDM analyses in the literature assume idealized receiver conditions in terms of time and frequency synchronization, and sampling clock offset. Moreover, often the cyclic prefix (CP) length is considered to be longer than the channel delay spread, and hence contributions from possible inter-symbol interference (ISI) in demodulation are not accounted for. This paper provides an aggregated framework to space frequency block coded (SFBC) MIMO-OFDM system performance by including major channel impairments and design issues such as insufficient CP against excess delay spread, sample timing error, frequency error, and time-varying fading. Transmit and receive filtering operations are also modeled, and bit error rate (BER) expressions are explicitly derived. We investigate different receiver detection schemes, diversity orders, and other key system parameters on BER. We also investigate the impact of excess delay spread on both channel and frequency-offset estimation. Cramer-Rao lower bounds (CRLB) are additionally derived and compared to assess the accuracy of the estimates. Along with a simple frequency offset detection technique, we derive channel and frequency offset estimation through the novel Recursive Nonlinear Dynamic Data Reconciliation (RNDDR) approach. Numerical results show improved performances of the RNDDR method compared to the traditional Kalman filter method for regular as well as step changes in parameters.

Large Doppler shifts are a challenge in underwater wireless acoustic communication compared to terrestrial wireless radio communication. Resampling and Doppler shift compensation are used at the receiver to counteract the effect of the Doppler shift introduced during transmission. Imperfect resampling can degrade system performance. While the conventional choice of Doppler compensation factor minimizes the intercarrier interference (ICI) around the central subcarrier, we show that using a Doppler compensation factor that treats lower subcarriers preferentially in terms of ICI can significantly improve the system performance in the case of imperfect resampling. Two ad-hoc schemes are proposed in the paper to find suitable Doppler compensation factors for a given Doppler factor and percentage of error in the resampling factor. The knowledge of these parameters facilitates the performance analysis of the schemes, rather than focusing on design aspects. The proposed schemes are tested for various relative vehicular speeds. In addition, different Doppler factors for the paths are considered. In all cases, our proposed schemes achieve higher video peak-signal-to-noise ratio compared to conventional schemes.

In one of our previous papers, we designed an ultra-low power non-coherent MFSK system using 2-pole bandpass filters to replace matched filters for detection and showed the performance loss between our proposed system and the optimal MFSK system using matched filters for detection was no greater than 1.2 dB in all alphabet size, phase continuity and channel conditions we analyzed. In this paper, we improve our previous design by considering the power-bandwidth tradeoff, and we show that we can save a large percentage of system bandwidth by sacrificing a small amount of power, when the demodulator and coding parameters are optimized. For example, we can save 50% of system bandwidth at the cost of 1 dB loss in performance compared to our previous system design. We further extend the results to include Gaussian filtering, we quantify the performance loss as a function of both the system bandwidth saved and the time-bandwidth product of the Gaussian filter, and we compare the performance of the $M$ -ary GFSK system with the corresponding MFSK system.

Spectrum sensing vulnerabilities in cognitive radio networks can significantly degrade performance. Most disruption attacks in the current literature involve spoofing of the free bands used for sensing by making them appear busy. In this study, we proposed a different approach for sensing disruptions. We examined the optimal strategy for an intelligent adversary with a given power to flip busy bands and make them appear free. The mechanism of sensing disruption was established by contaminating the noise power measurements. This is illustrated by a two-step sensing scheme in which energy detection, in conjunction with noise power estimation, is used by secondary users. We show that to flip busy bands, the optimal strategy for sensing link disruptions is equal-power, and partial-band flipping. We demonstrated that the maximum average number of missed detections can be derived under a constraint on power of the adversary. Through analytical and numerical results, we demonstrated the effectiveness of our approach in terms of the impact of disruption attacks on spectrum sensing.

Spectrum sharing disruption in cognitive radio networks (CRNs) can significantly degrade network performance. Most sharing disruption attacks in the literature focus on orthogonal multiple access (OMA) or higher layers, such as medium access control (MAC). However, this paper focuses on multi-carrier cognitive radio non-orthogonal multiple access (MC CR-NOMA). The sharing disruption mechanism is established by jamming the channel estimation phase. This is shown to cause a denial-of-service (DoS) for secondary users. We derive the optimal power allocation to disrupt spectrum sharing for a number of secondary users. This is demonstrated by deriving the maximum average number of DoS bands under a constraint on power of the adversary. Furthermore, a comparison between optimal power allocation and uniform power allocation is provided. Both the analytical and numerical results of the optimal sharing disruption are presented. Overall, this study highlights the vulnerabilities in spectrum sharing for MC CR-NOMA and presents a new type of attack.

This work investigates different subspace-based approaches for the equalization of signals transmitted from phase shift Distributed Beamforming systems. While phase shifters have been shown to be capable of enabling distributed beamforming by providing carrier coherence, it does not address mismatches in symbol timing, resulting in potentially significant levels of intersymbol interference. Using fractionally spaced receivers and the singular value decomposition of the channel matrix, we design linear and nonlinear equalization methods to combat the distortion induced by this symbol timing mismatch. We show that when linear equalization is not practical, a Causal Minimum Noise Decision Feedback Equalizer would provide us with better symbol error performance when operating with high signal-to-noise ratio, and we provide a lower bound on the error rate of this proposed equalization method.

We are interested in a communication system that operates in the presence of an intelligent jammer, under stringent power constraints, but with flexible bandwidth constraints.We optimize some of the key elements in the transceiver design for low power consumption, and thus high complexity components of the system, such as matched filters (MF), forward error correction (FEC) that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using M -ary frequency shift keying (MFSK) with non-coherent detection and fast frequency hopping (FFH), optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than the MF system with a performance loss of less than 1.4 dB for most scenarios that we considered. Further, the 2-pole BPF system can actually outperform the corresponding MF system by up to 2.4 dB in the presence of multi-tone jamming.

This letter presents tile-based wireless streaming of 360-degree videos with rate adaptation using viewport estimation. We propose a probabilistic model for viewport location to design importance weights of tiles. Based on the tile weights, we improve the streaming performance by dynamically adjusting quantization parameters and forward error correction rates across tiles.

A joint channel estimation and channel coding scheme is presented for channels with memory using polar codes. Unlike the conventional approach of first estimating all channel parameters and then performing channel decoding separately, the proposed scheme incorporates a subset of reliable estimates of channel parameters into the decoding procedure and computes decoding metrics averaged over the statistical behavior of the channel. Specifically, decoding algorithms for finite-state Markov channels of any order, for the Gauss-Markov channel and for flat-fading channels are presented. Further, by adapting list decoding to identify reliably-decoded bits within a codeword, channel estimation and decoding steps are performed iteratively to boost the reliability of channel estimation as well as error correction. In order to improve the performance even further, a new pilot arrangement scheme is developed that utilizes the structure of polar codes and sends pilot symbols embedded within the polar codewords. This construction can be viewed as a new family of shortened polar codes that can be of independent interest. Simulation results demonstrate the benefit of the proposed approach compared to existing solutions.

We study the transmission of high-quality video underwater. The underwater acoustic medium pathloss attenuation depends not only on transmission distance but also on the frequency occupied by the signal, where lower frequencies have lower attenuation for a given distance. We propose cross-layer design algorithms that exploit this frequency-dependent attenuation by connecting channel reliability to the structure of the compressed video. The video data are categorized based on their importance. Orthogonal frequency-division multiplexing is adopted as the modulation technique, such that different data can be sent on different frequencies. The underlying communications system accompanied with a noise analysis is developed in this article. The signal and noise statistics are used in the simulations to represent the underwater channel. We propose three new techniques and compare them to three baseline techniques. In the proposed techniques, important video information is transmitted on the least attenuated frequencies while less important data are transmitted through higher frequencies. Simulation results show that at least one of our proposed techniques can achieve significant improvements in the peak signal-to-noise ratio in comparison to the baseline techniques.

We are interested in a communication system that operates in a jamming environment under stringent power constraints, but is flexible with bandwidth constraints. Our approach is to consider some of the key elements in a transceiver and optimize them for low power consumption. An obvious consequence of this is that high complexity components of the system, such as matched filters, forward error correction (FEC) that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using $M$-ary FSK with non-coherent detection and fast frequency hopping (FFH), optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than an optimal one, and only lose at most 1.4 dB in terms of performance in most cases, compared to the conventional matched filter receiver.

An important indicator commonly used to evaluate the quality of a communication link is signal-to-interference ratio (SIR). However, studies in the literature dealing with SIR for orthogonal frequency division multiplexing (OFDM) systems are relatively few. This paper analytically investigates OFDM system performance by including major channel impairments such as excess delay spread, synchronization error, sample timing error, frequency offset, and time-varying fading. We derive a closed-form expression for SIR, accounting for both variations of inter-carrier interference (ICI) and inter-symbol interference (ISI) with the number of subcarriers, and the susceptibility to channel impairments. A condition relating peak ISI to peak ICI is derived. An expression quantifying the impact of synchronization error in ISI is obtained. SIR behavior with respect to the tradeoff among numbers of subcarriers and other system parameters are investigated. A numerical method, as well as a polynomial equation for an analytical solution, is formulated to find the optimal number of subcarriers for a given set of constraints. We demonstrate the variations of SIR with various parameters and analyze the leakage of power (unwanted power distribution across subcarriers).

We are interested in a communication system that operates under stringent power constraints, but is flexible with bandwidth constraints. Our approach is to consider some of the key elements in a transceiver and optimize them for low power consumption, as opposed to optimizing them to minimize, say, average probability of error. An obvious consequence of this is that high complexity components of the system, such as matched filters, forward error correction that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using M-ary FSK with non-coherent detection, optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than an optimal one, and only lose about 1.2 (M=16) to 1.5 (M=2) dB in terms of performance.

We consider incremental redundancy (IR) hybrid automatic repeat request (HARQ) over independent block-fading channels with turbo coding. We consider different cases of channel state information (CSI) at the transmitter: the transmitter has no knowledge of any CSI, or knows the CSI in previous transmission rounds through a perfect feedback channel, or knows both current and previous CSI. The transmitter decides the forward error correction code rate based on the CSI it has. We minimize the energy consumption of turbo-coded HARQ, subject to a packet loss rate constraint. Numerical results show that the energy consumption of HARQ decreases when more CSI information is available at the transmitter. We also compare IR combining with Chase combining and the system without combining, and IR combining yields the least energy consumption.

This paper proposes a joint source-channel rate-distortion (RD) optimization for real-time video transmission. The video compression and forward error correction (FEC) options are optimized by looking for the best trade-off between the estimated end-to-end distortion of a video packet and the sum of the number of source bits and FEC bits used to encode that packet. Video coding options include coding mode and quantization parameter, which are selected for each macroblock. Channel coding options consist of different FEC code rates that provide different levels of protection against the lossy channel. The proposed RD technique adjusts the bit rate to meet a target using a Lagrange multiplier approach. The encoder also uses the instantaneous channel state information to improve performance for a varying channel. Conventional RD optimization approaches optimize over the video coding modes, and our approach which considers the channel and FEC bits as well has better performance over both AWGN and Rayleigh fading channels. We also consider an approach to reduce the computational complexity of the proposed RD scheme.

We propose a robust spectrum sensing framework based on deep learning. The received signals at the secondary user's receiver are filtered, sampled and then directly fed into a convolutional neural network. Although this deep sensing is effective when operating in the same scenario as the collected training data, the sensing performance is degraded when it is applied in a different scenario with different wireless signals and propagation. We incorporate transfer learning into the framework to improve the robustness. Results validate the effectiveness as well as the robustness of the proposed deep spectrum sensing framework.

The impact of joint partial-time, partial-band jamming on a multicarrier (MC) asynchronous direct-sequence code-division multiple access (DS-CDMA) system in a fast fading environment is studied in conjunction with two different subcarrier combining and decoding schemes. An easy-to-evaluate upper bound using the Chernoff bound is provided and compared to simulation results. Simulation results suggest that for soft-decision decoding systems, under Rayleigh fading, full-time, full-band jamming is most effective. In contrast to the Rayleigh case, when a sufficiently strong line-of-sight component exists in the channel, the jammer's optimal strategy of attacking in time or frequency depends on the strength and the type of error correction that the system is deploying for that dimension. For hard-decision decoding systems, in Rayleigh fading, partial-band jamming is recommended. For the coding strategies examined, in Rician fading, the jammer should switch from full-time, partial-band jamming to a strategy that jams a higher percentage of the more heavily protected dimension as the jamming power increases. Furthermore, for AWGN channels, the results from the system show that the jammer should always jam a higher percentage of the more heavily protected dimension.

Deep modulation recognition has demonstrated high classification accuracy when a neural network is trained on large-scale datasets. However, when applied in an unknown environment where there are not any ground-truth labels in collected data, its performance can be significantly degraded. In this paper, we propose incorporating an adversarial discriminative neural network to adapt the deep modulation recognition to an unknown environment. Results show that, when the neural network is trained under an AWGN channel but applied under a frequency-selective Rayleigh fading channel, the adversarial network based domain adaptation can achieve comparable performance with that of the network trained with sufficiently large labeled data.

Different neural network (NN) architectures have different advantages. Convolutional neural networks (CNNs) achieved enormous success in computer vision, while recurrent neural networks (RNNs) gained popularity in speech recognition. It is not known which type of NN architecture is the best fit for classification of communication signals. In this work, we compare the behavior of fully-connected NN (FC), CNN, RNN, and bi-directional RNN (BiRNN) in a spectrum sensing task. The four NN architectures are compared on their detection performance, requirement of training data, computational complexity, and memory requirement. Given abundant training data and computational and memory resources, CNN, RNN, and BiRNN are shown to achieve similar performance. The performance of FC is worse than that of the other three types, except in the case where computational complexity is stringently limited.

Inthis paper we investigate energy-optimized wireless video transmission employing a hybrid automatic repeat request. We formulate the problem as maximizing the video quality, subject to a constraint on the wireless transmission energy consumption. We consider multiple parameters in multiple layers in a wireless video transmission system: transmit power, alphabet size, FEC code rate, maximum number of transmissions, and unequal video data importance. An analytical framework is proposed to include these parameters, which allows us to divide this problem into two sub-problems: data transmission and unequal error protection. The problem is tackled by solving the two sub-problems, which are done by exhaustive search and convex optimization, respectively. Simulations of different videos show that the proposed scheme outperforms methods using conventional data transmission and/or unequal error protection.