Communication Waveform Design Research Articles

A Power-Domain Non-Orthogonal Integrated Sensing and Communication Waveform Design Using OFDM

A Power-Domain Non-Orthogonal Integrated Sensing and Communication Waveform Design Using OFDM

Amplitude Barycenter Calibration of Delay-Doppler Spectrum for OTFS Signal—An Endeavor to Integrated Sensing and Communication Waveform Design

Amplitude Barycenter Calibration of Delay-Doppler Spectrum for OTFS Signal—An Endeavor to Integrated Sensing and Communication Waveform Design

Integrated sensing and communication waveform design in the Internet of Vehicles

We design an integrated sensing and communication (ISAC) transmission waveform with total transmission power, waveform similarity, and peak-to-average power ratio (PAPR) constraints in the Internet of Vehicles (IoV). The integrated waveform can complete radar target detection while communicating with downlink cellular users. The design of IoV with ISAC can not only improve the spectrum efficiency, but also further promote the integration of communication and sensing equipment. In this paper, the IoV with ISAC is formally modeled from the communication view and sensing view respectively. On this basis, taking the joint optimization of multi-user interference (MUI) total energy and Cramér Rao Bound (CRB) as the objective function, the transmission waveforms are designed with total transmission power, waveform similarity, and PAPR constraints respectively. To obtain the global optimal solution, we adopt a low complexity algorithm to solve the optimization problem under the total transmit power constraint and the optimization problem based on waveform similarity and PAPR constraints is further transformed into a nonconvex quadratically constrained quadratic programming (QCQP) problem, which is solved by using the semidefinite relaxation (SDR) technique. By ranking one approximation of the constrained optimization problem, it can be transformed into the solution of semidefinite programming (SDP) problems. The numerical results show that the designed ISAC transmission waveform can achieve an efficient tradeoff between sensing and communication performance, and each KPI is superior to one of the only communication and only sensing waveform design schemes. And it can improve the real-time information interaction ability of the IoV.

Integrated Sensing and Communication Waveform Design With Sparse Vector Coding: Low Sidelobes and Ultra Reliability

Integrated sensing and communication (ISAC) can provide efficient usage for both spectrum and hardware resources. A critical challenge, however, is to design the dual-functional waveform for simultaneous radar sensing and communication. In this paper, we propose a sparse vector coding-based ISAC (SVC-ISAC) waveform to simultaneously provide low sidelobes for radar sensing and ultra reliability for communication transmission. The key idea of the proposed waveform is to embed the communication information into the support of one sparse vector and transmit a low-dimensional signal via the spreading codebook. We derive a closed-form expression of the ambiguity function for the proposed SVC-ISAC waveform, and prove that it exhibits low sidelobes in the delay and Doppler domains, regardless of the distribution of the transmitted bit stream. In addition, the information decoding at the communication receiver is solved through the support identification and sparse demapping. Simulation results demonstrate that the proposed waveform improves the reliability while consistently suppressing the sidelobe levels.

Integrated Sensing and Communication Waveform Design: A Survey

Integrated sensing and communication (ISAC) has been widely recognized as a key technology in future sixth-generation (6G) wireless networks, especially for emerging applications and scenarios demanding both high-performance sensing and communication functionalities. The ISAC technique has the potential of enabling sensing and communication functionalities in a single hardware platform, even sharing the same waveform, thus, achieving the reduced cost of hardware implementation and the efficient use of spectrum resources. In this paper, we commence with the discussion on sensing and communication at the current stage from the view of motivations, applications, and challenges. Then, we provide a comprehensive survey of the state-of-the-art approaches to the ISAC technique from the waveform design perspective. To be specific, we classify the waveform design methods into three categories, namely, communication-centric waveform design, sensing-centric waveform design, and joint waveform optimization and design. In addition, potential research directions and challenges for future ISAC waveform design are outlined.

A New Radar-Embedded Communication Waveform with Low Computational Complexity

Radar-Embedded Communication (REC) is a covert communication technology that utilizes a radio frequency (RF) tag or transponder to embed the communication signal into the radar backscatter. The RF tag must be triggered by the radar signal and quickly generate the required communication waveforms so as to ensure that these communication symbols can be timely and effectively embedded in the radar backscatter pulse. Such an operation poses a great challenge to the response speed of the tag transponder. The traditional method is based on multiple eigenvalue decompositions to generate quasi-orthogonal communication waveforms, which requires a large amount of calculation. This paper proposes a strategy that requires only one eigenvalue decomposition operation. However, such a strategy makes it possible to generate completely orthogonal communication waveforms, and at the same time, it will contribute to a great reduction in the computational pressure of the RF tag. In addition, by simulation analyses, the communication waveform design strategy proposed in this paper does not take the reliability and the low probability of interception (LPI) of the waveform as the cost. On the contrary, under some conditions, communication reliability and LPI characteristics can be improved.

Integrated radar and communication waveform design based on a shared array

To reduce the consumption of spectrum and hardware resources, three methods are proposed to design the integrated radar and communication waveforms transmitted by a shared array. First, a minimum norm optimization (MNO) method is proposed to devise the transmit waveforms that can simultaneously synthesize desired radar and communication waveforms in different directions. The transmit beampattern formed by the designed waveforms has low sidelobe level (SLL). However, the designed waveforms may have high peak-to-average power ratio (PAPR). To reduce the PAPR, an iterative optimization (IO) method is proposed to devise the transmit waveforms with constant modulus. Then, to further reduce the SLL of the transmit beampattern formed by the designed constant modulus waveforms, the amplitude of each transmit waveform is iteratively optimized, which is referred to as iterative optimization with amplitude weighting (IO-AW) method. Finally, several numerical results show that the transmit waveforms designed by the proposed methods can simultaneously perform the radar and communication functions and can form the transmit beampattern with low SLL.

Tensor Communication Waveform Design With Semi-Blind Receiver in the MIMO System

A flexible mathematical framework for adaptive wireless communication waveform design is of importance for the implement of the cognitive radio-based software defined radio (CR-based SDR). As one of the popular models, the “spectrally modulated spectrally encoded” (SMSE) was proposed to tackle this problem but it cannot be trivially applied to the (massive) multiple input multiple output (MIMO) systems. In this paper, we extend the useful SMSE model into MIMO systems. Inspired by the tensor technique in signal processing and machine learning, we reformulate the desired waveforms as a higher-order tensors, of which the modes correspond to various modulation parameters such as coding chips, frequency and antennas. Beside the waveform design model, we further propose a new semi-blind receiver for the new model. Due the uniqueness of the applied tensor decomposition, we proved that the proposed receiver can jointly estimate the user symbols and channel state information without the aid of pilot sequences. Experimental results demonstrate the effectiveness of the proposed model in various communication scenes and outperforms the baseline systems. approximately 3 dB compared with the ideal receiver.

A New Shaped Waveform Design Scheme for Radar Embedded Communication

In order to improve the covertness of radar embedded communication based on the eigenvalue decomposition radar embedded communication waveform design scheme, a new waveform design scheme that combines the idea of shaped design is constructed. In this paper, the background and concept of radar embedded communication are introduced in detail. Three existing waveform design schemes are analyzed. Using de-correlation filter receivers, a weighted waveform design scheme for shaped non-dominant subspace feature vectors is constructed and analyzed. The communication covertness and reliability is illustrated. Both the theoretical analysis and the simulation show that this scheme improves the covertness of communication.

Modeling Contrast-Imaging-Assisted Optimal Targeted Drug Delivery: A Touchable Communication Channel Estimation and Waveform Design Perspective.

To maximize the effect of treatment and minimize the adverse effect on patients, we propose to optimize nanorobots-assisted targeted drug delivery (TDD) for locoregional treatment of tumor from the perspective of touchable communication channel estimation and waveform design. The drug particles are the information molecules; the loading/injection and unloading of the drug correspond to the transmitting and receiving processes; the concentration-time profile of the drug particles administered corresponds to the signaling pulse. Given this analogy, we first propose to use contrast-enhanced microwave imaging (CMI) as a pretherapeutic evaluation technique to determine the pharmacokinetic model of nanorobots-assisted TDD. The CMI system applies an information-theoretic-criteria-based algorithm to estimate drug accumulation in tumor, which is analogous to the estimation of channel impulse response in the communication context. Subsequently, we present three strategies for optimal targeted therapies from the communication waveform design perspective, which are based on minimization of residual drug molecules at the end of each therapeutic session (i.e., inter-symbol interference), maximization of duration when the drug intensity is above a prespecified threshold during each therapeutic session (i.e., non-fade duration), and minimization of average rate that a therapeutic operation is not received correctly at tumor (i.e., bit error rate). Finally, numerical examples are applied to demonstrate the effectiveness of the proposed analytical framework.

Communication Waveform Design Using an Adaptive Spectrally Modulated, Spectrally Encoded (SMSE) Framework

Fourth-generation (4G) communication systems will likely support multiple capabilities while providing universal, high-speed access. One potential enabler for these capabilities is software-defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved through a synergistic union called CR-based SDR. This paper introduces a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is one 4G candidate signal, OFDM-based signals are collectively classified as SMSE since data modulation and encoding are applied in the spectral domain. The proposed framework provides analytic commonality and unification of multiple SMSE signals. Framework applicability and flexibility is demonstrated for candidate 4G signals by: 1) showing that resultant analytic expressions are consistent with published results and 2) presenting representative modeling and simulation results to reinforce practical utility