Frequency-Packed Faster-Than-Nyquist Signaling via Symbol-Level Precoding for Multiuser MISO Redundant Transmissions

in IEEE Transactions on Wireless Communications (2022), 21(10), 8660-8674

This work addresses the issue of interference generated by co-channel users in downlink multi-antenna multicarrier systems with frequency-packed faster-than-Nyquist (FTN) signaling. The resulting ... [more ▼]

This work addresses the issue of interference generated by co-channel users in downlink multi-antenna multicarrier systems with frequency-packed faster-than-Nyquist (FTN) signaling. The resulting interference stems from an aggressive strategy for enhancing the throughput via frequency reuse across different users and the squeezing of signals in the time-frequency plane beyond the Nyquist limit. The spectral efficiency is proved to be increasing with the frequency packing and FTN acceleration factors. The lower bound for the FTN sampling period that guarantees information losslesness is derived as a function of the transmitting-filter roll-off factor, the frequency-packing factor, and the number of subcarriers. Space-time-frequency symbol-level precoders (SLPs) that trade off constructive and destructive interblock interference (IBI) at the single-antenna user terminals are proposed. Redundant elements are added as guard interval to cope with vestigial destructive IBI effects. The proposals can handle channels with delay spread longer than the multicarrier-symbol duration. The receiver architecture is simple, for it does not require digital multicarrier demodulation. Simulations indicate that the proposed SLP outperforms zero-forcing precoding and achieves a target balance between spectral and energy efficiencies by controlling the amount of added redundancy from zero (full IBI) to half (destructive IBI-free) the group delay of the equivalent channel. [less ▲]

Learning to Optimize: Balancing Two Conflict Metrics in MB-HTS Networks

in Advanced Satellite Multimedia Conference / Signal Processing for Space Communications Workshop (ASMS), Gratz, Viena, Sept. 2022 (2022, September)

RF Precoding for Cognitive Radio Systems

in IEEE Wireless Communications Letters (2022), 11(9), 1845-1849

In this letter, a precoding framework in the radio-frequency (RF) domain is developed for the downlink of a multiuser multiple-input single-output underlay cognitive radio (CR) system. Firstly, a low ... [more ▼]

In this letter, a precoding framework in the radio-frequency (RF) domain is developed for the downlink of a multiuser multiple-input single-output underlay cognitive radio (CR) system. Firstly, a low hardware complexity analog multiantenna architecture is proposed for the system’s transmitter. The proposed analog architecture is based on a phase-shifting network driven by an variable gain amplifier and has low power consumption since it avoids the use of energy hungry components such as digital-to-analog converters (DACs). Secondly, a novel RF precoder for the design of the transmit signals is developed such that the performance of the CR system is optimized and the constraints related to both the system’s architecture and the employed underlay CR paradigm are satisfied. The corresponding nonconvex and difficult optimization problem is formulated and solved via a novel algorithmic solution based on the saddle point method. The convergence of the proposed algorithmic solution is theoretically studied. The proposed approach is shown to be much more energy efficient than existing approaches based on fully digital transceivers. [less ▲]

Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks

in Bulletin. Cornell University Libraries (2022)

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs ... [more ▼]

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs than Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO) satellites. Moreover, LEO SatCom has the potential to provide global coverage with a high-speed data rate and low transmission latency. However, the spectrum scarcity might be one of the challenges in the growth of LEO satellites, impacting severe restrictions on developing ground-space integrated networks. To address this issue, cognitive radio and rate splitting multiple access (RSMA) are the two emerging technologies for high spectral efficiency and massive connectivity. This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt Karush–Kuhn–Tucker (KKT) conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. For comparison, we propose two suboptimal schemes with fixed power allocation over different beams and random resource block user assignment as the benchmark. Numerical results provided in this work are obtained based on the Monte Carlo simulations, which demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes. [less ▲]

Robust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications

in IEEE Transactions on Communications (2022)

Energy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications under Imperfect CSI

in IEEE Transactions on Intelligent Transportation Systems (2022)

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and ... [more ▼]

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and other devices. Recently, ambient backscatter communications (AmBC) have gained significant interest in the research community for providing battery-free communications. AmBC can modulate useful data and reflect it towards near devices using the energy and frequency of existing RF signals. However, obtaining channel state information (CSI) for AmBC systems would be very challenging due to no pilot sequences and limited power. As one of the latest members of multiple access technology, non-orthogonal multiple access (NOMA) has emerged as a promising solution for connecting large-scale devices over the same spectral resources in B5G wireless networks. Under imperfect CSI, this paper provides a new optimization framework for energy-efficient transmission in AmBC enhanced NOMA cooperative vehicle-to-everything (V2X) networks. We simultaneously minimize the total transmit power of the V2X network by optimizing the power allocation at BS and reflection coefficient at backscatter sensors while guaranteeing the individual quality of services. The problem of total power minimization is formulated as non-convex optimization and coupled on multiple variables, making it complex and challenging. Therefore, we first decouple the original problem into two sub-problems and convert the nonlinear rate constraints into linear constraints. Then, we adopt the iterative sub-gradient method to obtain an efficient solution. For comparison, we also present a conventional NOMA cooperative V2X network without AmBC. Simulation results show the benefits of our proposed AmBC enhanced NOMA cooperative V2X network in terms of total achievable energy efficiency. [less ▲]

Resource Allocation in Heterogeneously-Distributed Joint Radar-Communications Under Asynchronous Bayesian Tracking Framework

in IEEE Journal on Selected Areas in Communications (2022), 40(7), 2026-2042

Optimal allocation of shared resources is key to deliver the promise of jointly operating radar and communications systems. In this paper, unlike prior works which examine synergistic access to resources ... [more ▼]

Optimal allocation of shared resources is key to deliver the promise of jointly operating radar and communications systems. In this paper, unlike prior works which examine synergistic access to resources in colocated joint radar-communications or among identical systems, we investigate this problem for a distributed system comprising heterogeneous radars and multi-tier communications. In particular, we focus on resource allocation in the context of multi-target tracking (MTT) while maintaining stable communications connections. By simultaneously allocating the available power, dwell time and shared bandwidth, we improve the MTT performance under a Bayesian tracking framework and guarantee the communications throughput. Our a lter n ating allo c ation of h eterogene o us r esources (ANCHOR) approach solves the resulting non-convex problem based on the alternating optimization method that monotonically improves the Bayesian Cramér-Rao bound. Numerical experiments demonstrate that ANCHOR significantly improves the tracking error over two baseline allocations and stability under different target scenarios and radar-communications network distributions. [less ▲]

Backscatter-Aided NOMA V2X Communication under Channel Estimation Errors

Scientific Conference (2022, June 20)

Backscatter communications (BC) has emerged as a promising technology for providing low-powered transmissions in nextG (i.e., beyond 5G) wireless networks. The fundamental idea of BC is the possibility of ... [more ▼]

Backscatter communications (BC) has emerged as a promising technology for providing low-powered transmissions in nextG (i.e., beyond 5G) wireless networks. The fundamental idea of BC is the possibility of communications among wireless devices by using the existing ambient radio frequency signals. Non-orthogonal multiple access (NOMA) has recently attracted significant attention due to its high spectral efficiency and massive connectivity. This paper proposes a new optimization framework to minimize total transmit power of BC-NOMA cooperative vehicle-to-everything networks (V2XneT) while ensuring the quality of services. More specifically, the base station (BS) transmits a superimposed signal to its associated roadside units (RSUs) in the first time slot. Then the RSUs transmit the superimposed signal to their serving vehicles in the second time slot exploiting decode and forward protocol. A backscatter device (BD) in the coverage area of RSU also receives the superimposed signal and reflect it towards vehicles by modulating own information. Thus, the objective is to simultaneously optimize the transmit power of BS and RSUs along with reflection coefficient of BDs under perfect and imperfect channel state information. The problem of energy efficiency is formulated as non-convex and coupled on multiple optimization variables which makes it very complex and hard to solve. Therefore, we first transform and decouple the original problem into two sub-problems and then employ iterative sub-gradient method to obtain an efficient solution. Simulation results demonstrate that the proposed BC-NOMA V2XneT provides high energy efficiency than the conventional NOMA V2XneT without BC. [less ▲]

Area-Power Analysis of FFT Based Digital Beamforming for GEO, MEO, and LEO Scenarios

in Area-Power Analysis of FFT Based Digital Beamforming for GEO, MEO, and LEO Scenarios (2022, June 19)

Satellite communication systems can provide seamless wireless coverage directly or through complementary ground terrestrial components and are projected to be incorporated into future wireless networks ... [more ▼]

Satellite communication systems can provide seamless wireless coverage directly or through complementary ground terrestrial components and are projected to be incorporated into future wireless networks, particularly 5G and beyond networks. Increased capacity and flexibility in telecom satellite payloads based on classic radio frequency technology have traditionally translated into increased power consumption and dissipation. Much of the analog hardware in a satellite communications payload can be replaced with highly integrated digital components that are often smaller, lighter, and less expensive, as well as software reprogrammable. Digital beamforming of thousands of beams simultaneously is not practical due to the limited power available onboard satellite processors. Reduced digital beamforming power consumption would enable the deployment of a full digital payload, resulting in comprehensive user applications. Beamforming can be implemented using matrix multiplication, hybrid methodology, or a discrete Fourier transform (DFT). Implementing DFT via fast Fourier transform (FFT) reduces the power consumption, process time, hardware requirements, and chip area. Therefore, in this paper, area-power efficient FFT architectures for digital beamforming are analyzed. The area in terms of look up tables (LUTs) is estimated and compared among conventional FFT, fully unrolled FFT, and a 4-bit quantized twiddle factor (TF) FFT. Further, for the typical satellite scenarios, area, and power estimation are reported. [less ▲]

Effective Rate of RIS-aided Networks with Location and Phase Estimation Uncertainty

in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC) (2022, May)