Incorporating Cross-Ambiguity Function-Based Radar in Wireless Orthogonal Frequency-Division Multiplexing Communication Receivers [Tips & Tricks

Channel estimation is a well-known challenge for wireless orthogonal frequency division multiplexing (OFDM) communication systems with massive antennas on high speed rails (HSRs). This paper investigates this problem and design two practicable uplink and downlink channel estimators for orthogonal frequency division multiplexing (OFDM) communication systems with massive antenna arrays at base station on HSRs. Specifically, we first use pilots to estimate the initial angle of arrival (AoA) and channel gain information of each uplink path through discrete Fourier transform (DFT), and then refine the estimates via the angle rotation technique and suggested pilot design. Based on the uplink angel estimation, we design a new downlink channel estimator for frequency division duplexing (FDD) systems. Additionally, we derive the Cramér-Rao lower bounds (CRLBs) of the AoA and channel gain estimates. Finally, numerical results are provided to corroborate our proposed studies.

This paper considers the problem of physical layer security of a wireless orthogonal frequency division multiplexing (OFDM) communication system. We first develop a transmit filter-aided secure OFDM system scheme which can disturb eavesdropper's receptions by destroying the orthogonality of OFDM signals at the eavesdropper, while the quality of legitimate transmission is maintained. Then, in an effort to further improve the security performance, we also propose an artificial noise (AN)-aided secure OFDM system associated with the transmit filter-aided approach. AN is generated in the null space of the legitimate channel by making use of residual power after power allocation for subcarriers. Therefore, AN can only disrupt eavesdropper's receptions but not affect legitimate receiver. Simulation results are presented to illustrate the efficiency of the proposed transmit filter and AN-aided physical layer security designs in the OFDM wiretap system.

<span lang="EN-US">The peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) communication system will be reduced using reconfigurable peak cancellation (RPC). RPC will also aid in improves the error vector magnitude (EVM) and reduces adjacent channel leakage ratio (ACLR) in OFDM communication system. The proposed RPC design methodology and practical implementation using field programmable gate array (FPGA) are discussed. The proposed RPC has been demonstrated using VIRTEX-7 XC7Z100 dual-core FPGA device with less hardware difficulty and minimum utilization of FPGA resources. The proposed RPC improves the efficiency of OFDM communication process by reducing complementary cumulative distribution function (CCDF) with respect to instantaneous power in dB. A comparison analysis was done between the existing selective mapping (SLM) method with proposed RPS method with respect FPGA resource utilization. The proposed RPC is implemented using VIRTEX-7 XC7Z100 dual-core FPGA device. Its effectively utilizing sub-carriers, fast Fourier transform (FFT) filter, bandwidth, and sampling frequency. Due to parallel switching operation, it reduces the PAPR, ACLR and improves EVM in OFDM signal with less hardware complexity.</span>

An adaptive pilot-symbol assignment scheme is proposed for interpolation-based channel estimation in wireless orthogonal frequency division multiplexing (OFDM) communication systems. The channel transfer functions of data tones are interpolated by the piecewise-linear and the second-order polynomial methods due to their inherent simplicity. Simulations are conducted to demonstrate both system performance and bandwidth (BW) superiority and to provide a comparative evaluation of the proposed scheme with conventional fixed pilot-symbol channel estimation schemes.

This tutorial paper addresses the physical layer security concerns and resiliency of Orthogonal Frequency Division Multiplexing (OFDM) communications; the de facto air-interface of most modern wireless broadband standards including 3GPP Long Term Evolution (LTE) and WiMAX. The paper starts with a brief introduction to the OFDM waveform and then reviews the robustness of the existing OFDM waveform in the presence of noise, multipath fading, and interference. The paper then moves on to build comprehensive adversarial models against OFDM waveforms. Robustness of OFDM is first investigated under AWGN noise and noise-like jamming attack scenarios, then under uncorrelated yet colored interferences from modulated sources (both intentional and unintentional). Finally, the paper explores some of the more recent developments in the field of energy efficient correlated jamming attacks that can disrupt communication severely by exploiting the knowledge of the target waveform structure. Potential countermeasures against such jamming attacks are presented, in an attempt to make a robust and resilient OFDM waveform.

Sampling frequency synchronization in orthogonal frequency division multiplexing (OFDM) communications is critical for achieving the full advantages offered by this modulation scheme. In this paper, we propose a novel and efficient, blind, cyclostationarity-based sampling frequency synchronization (CB-SFS) algorithm for estimating the sampling frequency offset (SFO) in OFDM communications by exploiting the relationship between the sampling frequency and the cyclostationary properties of the sampled received signal. The proposed scheme is ignorant of the channel coefficients and does not require pilots. These two properties are rather unique in this context and are not possessed by previous schemes which achieve comparable estimation performance. These properties also make the proposed CB-SFS scheme suitable for a wide range of communications scenarios. The main novelty of the new scheme is the understanding that SFO alters the cycle frequencies at the receiver, yet these frequencies are a priori known for the discrete-time (DT) transmitted signal, as they result from the periodic operation of the DT signal generation scheme at the transmitter. We show that the mismatch between the measured and the expected cycle frequencies is directly related to the SFO. Complexity analysis and numerical simulations are carried out and demonstrate the superiority of the proposed CB-SFS algorithm compared to the existing approaches. It is illustrated that the proposed algorithm can achieve a smaller estimation error at the same complexity order of current algorithms while providing a higher spectral efficiency and robustness to additive stationary noise and to multipath.

This paper presents an Application-Specific Signal Processor (ASSP) for Orthogonal Frequency Division Multiplexing (OFDM) Communication Systems, called SPOCS. The instruction set and its architecture are specially designed for OFDM systems, such as Fast Fourier Transform (FFT), scrambling/descrambling, puncturing, convolutional encoding, interleaving/deinterleaving, etc. SPOCS employs the optimized Data Processing Unit (DPU) to support the proposed instructions and the FFT Address Generation Unit (FAGU) to automatically calculate input/output data addresses. In addition, the proposed Bit Manipulation Unit (BMU) supports efficient bit manipulation operations. SPOCS has been synthesized using the SEC 0.18 μm standard cell library and has a much smaller area than commercial DSP chips. SPOCS can reduce the number of clock cycles over 8%~53% for FFT and about 48%~84% for scrambling, convolutional encoding and interleaving compared with existing DSP chips. SPOCS can support various OFDM communication standards, such as Wireless Local Area Network (WLAN), Digital Audio Broadcasting (DAB), Digital Video Broadcasting-Terrestrial (DVB-T), etc.

Peak-to-average power ratio (PAPR) is an important indicator of orthogonal frequency division multiplexing (OFDM) communication system. In order to improve the power efficiency of the OFDM system transmitter, it is desirable that PAPR will be as small as possible. In this paper, a kind of hybrid sequence set with PAPR equal to 3dB is proposed. The proposed hybrid sequence set consists of two sequence subsets, namely a binary real sequence subset and its corresponding complex sequence subset. When such hybrid sequence set is used in a M-ary spread spectrum (MSS) OFDM communication system, the data rate of the MSS-OFDM system will be improved without any increase in PAPR. The construction method of PAPR-3dB hybrid sequence set is provided in this paper, and its corresponding performance is analyzed. Simulation results show the efficiency of the proposed method.

Besides avoiding inter-symbol interference and leading to high capacity, wireless orthogonal frequency division multiplexing (OFDM) provide fine granularity for resource allocation since they are capable of dynamically assigning sub-carriers to multiple users and adaptively allocating transmit power. The current dominate layered networking architecture, in which each layer is designed and operated independently, results in inefficient and inflexible resource use in wireless networks due to the nature of the wireless medium, such as time-varying channel fading. Thus, we need an integrated adaptive design across different layers. In this paper, we focus on resource allocation and scheduling in wireless multiuser OFDM networks based on joint physical and medium access control (MAC) layer optimization. An adaptive cross-layer design for the downlink multiuser OFDM systems, to maximize the weighted sum capacity of all users, where each user has multiple heterogeneous traffic queues simultaneously is proposed. A packet dependent (PD) scheduling scheme is employed at the MAC layer, which determines the packet transmission order by assigning different weights to different packets, and is shown by simulations more efficient than the previous methods where all packets in a queue have the same weight. The weight design in PD scheduling considers the delay, size and quality of service (QoS) priority level of packets. Each user weight employed in resource allocation at the physical (PHY) layer is obtained by summing up the weights of selected packets for the user. We also deeply investigate the various resource scheduling schemes for comparisons.

This manuscript addresses the maximum-a-posteriori-(MAP)-based automatic modulation classification (AMC) for wireless orthogonal frequency division multiplexing (OFDM) systems with adaptive coding and modulation (ACM). The proposed classifier for quadrature amplitude modulation (QAM) schemes which utilizes the channel reciprocity in time-division duplex (TDD) systems requires the knowledge about the joint probabilities of the subcarrier-wise bit efficiencies at the transmitter and receiver side. In contrast to prior heuristic approaches, these probabilities are calculated analytically (with some approximations) if the transmitter and receiver apply the same bit loading algorithm on their erroneously estimated channel state information. Numerical results reveal that the precise knowledge of the joint probabilities improves the reliability of the automatic modulation classifier significantly, especially for high signal-to-noise power ratios (SNR).

Deep learning based underwater acoustic OFDM communications

For Orthogonal Frequency Division Multiplexing (OFDM) and other communication systems, many estimating approaches have been developed to estimate the channel state information and lower the Bit Error Rate (BER). These estimating methods, however, are still subject to the influence of large peak powers compared to average powers. Reduced computational complexity is one of the most significant factors to consider while developing a new estimate algorithm. This study aims to provide a novel design of the Packet-Discrete Wavelet Transform (P-DWT) algorithm for channel estimation in wireless OFDM instead of the fast Fourier transform (FFT). It is presented to retrieve the code of a spread spectrum signal and transmitted data bits, and it is compared to particle swarm optimization PSO and least mean square (LMS) optimization. The suggested approach reduces the computing cost of DWT by recognizing the Packet Wavelet Transform (PWT) coefficients and local points, findings utilizing P-DWT channels generated from both models and measurements show that the proposed technique outperforms pilot-based channel estimation in terms of bit error rate under sparseness conditions BER. Moreover, as compared to typical semi-blind approaches, the estimation accuracy is enhanced while computing cost is reduced.

To perform the integration of radar and communication in waveform, we design an integrated system combining multiple-input multiple-output radar with orthogonal frequency division multiplexing (OFDM) communication. In this system, each antenna transmits the integrated waveform with a nonoverlapping block sub-frequency band. The utilized waveform is a variation of the classical OFDM communication waveform. In order to sufficiently exploit the entire system bandwidth and array aperture, a joint time and space processing approach is proposed, and hence the range and angle estimations with high resolution are obtained, whereas the range and angle are coupled. Moreover, the loss in processing gain and the Cramer–Rao bounds of range and angle estimates based on integrated waveform are derived, respectively. Theoretical analysis validates that the designed system is capable of implementing the radar and communication functions simultaneously. Finally, numerical results are presented to verify the effectiveness of the proposed approach.

OFDM (orthogonal frequency division multiplexing) communication is very attractive for high data rate transmission especially in the frequency selective fading channel. However, OFDM signal may be distorted by the nonlinear HPA (high power amplifier) since it has very high PAPR (peak-to-average power ratio). The proposed method is basically similar to the conventional SLM (selective mapping) method. However, the selected dummy sequences instead of the phase rotation sequence are inserted to reduce the PAPR in the OFDM communication system. So, we propose a modified SLM method in which complementary sequence or other kind of dummy sequence produced by flipping method can be inserted at the predefined sub-carriers. After IFFT (inverse fast Fourier transform), the OFDM data signal with the lowest PAPR is selected for transmission like the SLM method. Unlike the conventional PTS (partial transmit sequence) and SLM, it is needless to transmit and recover the side information about the phase rotation. Also, it can be free from the computational burden caused by finding the phase rotation factor for peak value optimization and time delay problem can be additionally solved

Recently multi-carrier orthogonal frequency division multiplexing (OFDM) communications, popularly used in wireless channels, has been introduced in underwater acoustic channels with a large delay spread, as an alternative to the typical single carrier approaches. In this paper, we investigate multiple-input/multiple-output (MIMO) OFDM communications which can effectively increase the data rate in band-limited underwater channels. The performance of MIMO OFDM communications will be illustrated using the data collected from the KAM11 experiment conducted in shallow water, west of Kauai, Hawaii, which involved multiple transmit and receive arrays with different bandwidths, inter-element spacings, and apertures at various ranges between them up to 10 km.