Concurrent Transmissions Research Articles

Joint Energy Loss and Time Span Minimization for Energy-Redistribution-Assisted Charging of WRSNs With a Mobile Charger

The use of mobile chargers (MCs) to charge the nodes in wireless rechargeable sensor networks via wireless power transfer (WPT) has attracted much research effort. Existing works mostly concentrate on path planning whereas neglecting the opportunities to improve charging coverage and efficiency by exploiting the energy redistribution (ERD) process among nodes and an MC’s capability of charging multiple nodes simultaneously via WPT. To exploit such opportunities, we study the underlying ERD-assisted MC charge scheduling (ERAMCCS) problem, i.e., to find a charging schedule satisfying the nodes’ energy demands with minimum energy loss and minimum time span. After proving that the problem is NP-hard, we propose a charge scheduling algorithm based on the greedy idea (CSBGI), which provides a solution by decoupling the problem into two subproblems: 1) ERAMCCS-Energy and 2) ERAMCCS-Time, to minimize the energy loss and the time span, respectively. By partitioning the energy loss into transmission energy loss and moving energy loss, we solve the ERAMCCS-Energy problem by minimizing the two parts, respectively, by formulating and solving some linear programming problems and traveling salesman problem problems based on the charging position set. The charging position set is iteratively refined by identifying and removing redundant charging positions. For the ERAMCCS-Time problem, concurrent energy transmission opportunities are exploited to try to minimize the time span of the schedule. We demonstrate some key properties of CSBGI, such as its approximation ratio in terms of energy loss and its time complexity. Testbed experiments and numerical simulations confirm the superiority of CSBGI over typical algorithms.

Concurrent Transmission and Multiuser Detection of LoRa Signals

This article investigates a new model to improve the scalability of low-power long-range (LoRa) networks by allowing a group of multiple end devices (EDs) to communicate with multiple multi-antenna gateways simultaneously (i.e., in the same time slot) on the same frequency band and using the same spreading factor. The maximum-likelihood (ML) decision rule is first derived for noncoherent detection of information bits transmitted by multiple devices in a group. To overcome the high complexity of the ML detection, we propose a suboptimal two-stage detection algorithm to balance the computational complexity and error performance. In the first stage, we identify transmitted chirps (without knowing which EDs transmit them). In the second stage, we determine the EDs that transmit the specific chirps identified from the first stage. To improve the detection performance in the second stage, we also optimize the transmit powers of EDs to minimize the similarity, measured by the Jaccard coefficient, between the received powers of any pair of EDs in the same group. As the power control optimization problem is nonconvex, we use concepts from successive convex approximation to transform it to an approximate convex optimization problem that can be solved iteratively and guaranteed to reach a suboptimal solution. Simulation results demonstrate and justify the tradeoff between transmit power penalties and network scalability of the proposed LoRa network model. In particular, by grouping two or three EDs in each group for concurrent transmission, the uplink capacity of the proposed network can be doubled or tripled over that of a conventional LoRa network, albeit at the expense of additional 3.0 or 4.7 dB transmit power.

Cooperative Gigabit Content Distribution with Network Coding for mmWave Vehicular Networks

Millimeter-wave (mmWave) directional communication has been deemed as a promising means to achieve the goal of multi-gigabit data rate with low latency in vehicular ad-hoc networks (VANETs). However, due to the frequent transmission errors caused by the lossy nature of mmWave wireless links and high dynamic of VANETs, the channel resources are not fully exploited. In order to enhance the resilience to transmission errors, we introduce the symbol level network coding (SLNC) to mmWave wireless communications. We propose a greedy network coding strategy based on graph-theoretic approach, named GTNC, so as to take full advantage of SLNC. Moreover, considering the directionality of mmWave and the effect of GTNC on degrading transmission redundancy, it has great potential to realize concurrent transmission in mmWave vehicular networks. Therefore, we propose a cooperative concurrent distribution scheme with GTNC, named CCDS-GTNC, to coordinate transmissions between vehicles, which carries out collaborative vehicle-to-vehicle (V2V) and vehicle-to-Infrastructure (V2I) communications and achieves concurrent transmissions of multiple transmitters simultaneously. The simulation results show that our proposed scheme can effectively improve the efficiency of content dissemination in view of reducing the transmission delay and transmission redundancy.

A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges

Long-range (LoRa) technology is most widely used for enabling low-power wide area networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides extensive coverage for low-power devices, making it an ideal communication system for many internet of things (IoT) applications. In general, LoRa is considered as the physical layer, whereas LoRaWAN is the medium access control (MAC) layer of the LoRa stack that adopts a star topology to enable communication between multiple end devices (EDs) and the network gateway. The chirp spread spectrum modulation deals with LoRa signal interference and ensures long-range communication. At the same time, the adaptive data rate mechanism allows EDs to dynamically alter some LoRa features, such as the spreading factor (SF), code rate, and carrier frequency to address the time variance of communication conditions in dense networks. Despite the high LoRa connectivity demand, LoRa signals interference and concurrent transmission collisions are major limitations. Therefore, to enhance LoRaWAN capacity, the LoRa Alliance released many LoRaWAN versions, and the research community has provided numerous solutions to develop scalable LoRaWAN technology. Hence, we thoroughly examine LoRaWAN scalability challenges and state-of-the-art solutions in both the physical and MAC layers. These solutions primarily rely on SF, logical, and frequency channel assignment, whereas others propose new network topologies or implement signal processing schemes to cancel the interference and allow LoRaWAN to connect more EDs efficiently. A summary of the existing solutions in the literature is provided at the end of the paper, describing the advantages and disadvantages of each solution and suggesting possible enhancements as future research directions.

Opportunistic Symbiotic Backscatter Communication Systems

This letter proposes an opportunistic commensal mechanism (OppCom) and an opportunistic parasitic mechanism (OppPar) for a pair of backscatter devices (BDs) to strengthen the concurrent transmission of the primary and the backscatter systems. It is shown that the asymptotic outage probability of the OppCom and OppPar mechanisms is not affected by the channel statistics between the two BDs. Also, for the OppPar mechanism, the backscatter efficiency ratio between the two BDs, instead of their individual values, dominates the system outage performance and a larger difference of the backscatter efficiencies leads to a better transmission robustness.

Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role Can RIS Play?

With the aim of integrating over-the-air federated learning (AirFL) and non-orthogonal multiple access (NOMA) into an on-demand universal framework, this paper proposes a novel reconfigurable intelligent surface (RIS)-aided hybrid network by leveraging the RIS to flexibly adjust the signal processing order of heterogeneous data. The objective of this work is to maximize the achievable hybrid rate by jointly optimizing the transmit power, controlling the receive scalar, and designing the phase shifts. Since the concurrent transmissions of all computation and communication signals are aided by the discrete phase shifts at the RIS, the considered problem (P0) is a challenging mixed integer programming problem. To tackle this intractable issue, we decompose the original problem (P0) into a non-convex problem (P1) and a combinatorial problem (P2), which are characterized by the continuous and discrete variables, respectively. For the transceiver design problem (P1), the power allocation subproblem is first solved by invoking the difference-of-convex programming, and then the receive control subproblem is addressed by using the successive convex approximation, where the closed-form expressions of simplified cases are derived to obtain deep insights. For the reflection design problem (P2), the relaxation-then-quantization method is adopted to find a suboptimal solution for striking a trade-off between complexity and performance. Afterwards, an alternating optimization algorithm is developed to solve the non-linear and non-convex problem (P0) iteratively. Finally, simulation results reveal that 1) the proposed RIS-aided hybrid network can support the on-demand communication and computation efficiently, 2) the performance gains can be improved by properly selecting the location of the RIS, and 3) the designed algorithms are also applicable to conventional networks with only AirFL or NOMA users.

PCube: Scaling LoRa Concurrent Transmissions with Reception Diversities

This article presents the design and implementation of PCube, a phase-based parallel packet decoder for concurrent transmissions of LoRa nodes. The key enabling technology behind PCube is a novel air-channel phase measurement technique that is able to extract phase differences of air-channels between LoRa nodes and multiple antennas of a gateway. PCube leverages the reception diversities of multiple receiving antennas of a gateway and scales the concurrent transmissions of a large number of LoRa nodes, even exceeding the number of receiving antennas at a gateway. As a phase-based parallel decoder, PCube provides a new dimension to resolve collisions and supports more concurrent transmissions by complementing time and frequency-based parallel decoders. PCube is implemented and evaluated with synchronized software defined radios and off-the-shelf LoRa nodes in both indoors and outdoors. Results demonstrate that PCube can substantially outperform state-of-the-art works in terms of aggregated throughput by 4.9× and the number of concurrent nodes by up to 5×. More importantly, PCube scales well with the number of receiving antennas of a gateway, which is promising to break the barrier of concurrent transmissions.

A Hierarchy-Based Energy-Efficient Routing Protocol for LoRa-Mesh Network

LoRa is one of the most promising techniques for the Internet of Things (IoT), and it has attracted considerable attention. Most existing LoRa applications follow the LoRaWAN specification and adopt a star topology. However, LoRaWAN networks are typically limited by their scalability due to the use of a centralized control strategy. The recent development of LoRa-Mesh networks can be a potential solution to this limitation. In this article, we propose a hierarchical-based energy-efficient (HBEE) routing protocol as a desirable method for building LoRa-Mesh networks. The HBEE exhibits the following advantages: 1) it can quickly build the network structure during the network formation stage by using contention-free concurrent transmission; 2) during the routing exploration phase, end-device nodes (ENs) can locate parent ENs with a minimized overhead; and 3) at the data collection stage, packet collision is minimized using multipath and multichannel routing method. Simulations are conducted to evaluate the performance of HBEE, and the results show that HBEE outperforms conventional ad hoc on-demand distance vector routing (AODV) protocol in terms of energy efficiency and transmission delay. Finally, proof-of-concept experiments are implemented in the real world. The results show that the packet reception rate of 95.7% and 89.8% can be achieved during network formation and normal operation phases, respectively.

A virtual gateway media access placement approach for large-scale Internet of Things

The virtualisation of the Internet of Things (IoT) Gateway (GW) Media Access Control (MAC) component separates the GW MAC functions from the GW device by deploying the GW MAC functions in a selected remote edge Data Centre (eDC). This concept can help support media access for a large number of devices based on concurrent transmissions over Radio Frequency (RF) virtualisation. However, the requests for virtual GW MAC instances are dynamic and the virtual network is characterised by varying resource levels and response times. This can affect the throughput performance of the MAC protocol since the timing deadlines of the MAC functions or frame transmissions may not be met. In this work, the GW MAC functions of the IEEE 802.11ah standard for Large Scale IoT (LS-IoT) networks are virtualised as concurrent virtual Access Groups (vAGs) over a proposed Software Defined Network (SDN) virtual network. A virtual GW MAC placement strategy is proposed to optimally select the host for running the virtual GW MAC instances to minimise the virtualisation delay, improve the robustness of the deployment process and maintain a good MAC throughput performance. The results obtained in this work show that the virtualisation delay is minimised and the MAC throughput versus the number of devices is improved especially for high IoT traffic rates when compared to suboptimal approaches and the dedicated localised GW MAC approach.

On-Chip Optical Routing With Provably Good Algorithms for Path Clustering and Assignment

As the VLSI technology continues to scale down, combined with increasing demands for large bandwidth and low-power consumption, the optical interconnections with wavelength-division multiplexing (WDM) become an attractive alternative for on-chip signal transmission. Previous WDM-aware optical routing works consist of three main drawbacks: they are based mainly on heuristics or restricted integer linear programming to handle optical routing, the addressed types of insertion loss, and WDM overheads are incomplete, and the crosstalk noise during concurrent signal transmission is neglected. As a result, no performance guarantees can be achieved on their WDM clustering results, the reliability of the optical network is impaired, and/or their computations are too time consuming. To remedy these disadvantages, we present a new WDM-aware optical routing flow to minimize the insertion loss, the WDM overheads, and the crosstalk noise with a significant speedup. In the proposed flow, the WDM-aware path clustering algorithm guarantees to find an optimal solution for 1-, 2-, and 3-path clustering and has the constant performance bound for most cases of 4-path clustering; the crosstalk-aware path assignment guarantees to minimize the number of crosstalk signal pairs within the given displacement bound. Experimental results based on the ISPD 2007 and 2019 contest benchmarks and a real optical design show that our optical router significantly outperforms published works in wirelength, insertion loss, wavelength power, crosstalk noise, and runtimes.

Framed Fidelity MAC: Losslessly packing multi-user transmissions in a virtual point-to-point framework

As the number of subscribers in wireless communication systems grows rapidly, it has become important to design efficient medium access control (MAC) protocols to realize resources sharing among multiple users. When designing a MAC, effective management of co-channel interference (CCI) among multiple concurrent transmissions is critical to enhancing system’s spectral efficiency (SE). Although MACs based on existing signal processing can suppress/mitigate CCI among multiple concurrent transmissions, they either consume communication resources or attenuate the desired signals’ transmission, hence incurring loss of transmission performance. To remedy this deficiency, we propose a Framed Fidelity MAC (F2MAC) to losslessly pack multi-user data transmissions into a virtual point-to-point (p2p) framework. Under F2MAC, the common receiver (Rx) selects a virtual framed-channel (a.k.a. framework) and broadcasts it to all mobile terminals. The latter calculate their precoding vectors based on the received virtual framework and their respective communication channels with respect to (w.r.t.) the Rx. Then, the pre-processed signals of multiple users are sent to the Rx via different eigenmodes of the framed-channel. By applying a receive filter to the received mixed signal, Rx can recover users’ desired data without interference. Since F2MAC can decouple the channel quality information (CQI) from channel direction information (CDI) related to the user’s signal transmission, — i.e., CQI is exclusively determined by the user’s communication channel while CDI depends on the unified framework, it can avoid the transmission performance loss incurred by existing signal processing based MAC which adjusts both CQI and CDI simultaneously. Moreover, we propose a Flexible Framed Fidelity MAC (F3MAC) to further improve the system’s SE. By dynamically re-constructing the virtual framed-channel at each mobile user, the user’s transmission can be realized with the principal eigenmode’s gain of his/her communication channel. Our in-depth analysis and simulation results have shown the proposed MAC methods to significantly improve the SE of multi-user communication systems.

Optimal Achievable Transmission Capacity Scheme for Full-Duplex Multihop Wireless Networks.

Full-duplex (FD) communication has been attractive as the breakthrough technology for improving attainable spectral efficiency since the 5G mobile communication system. Previous research focused on self-interference cancellation and medium access control (MAC) protocol to realize the FD system in wireless networks. This paper proposes an optimal achievable transmission capacity (OATC) scheme for capacity optimization in the FD multihop wireless networks. In this paper, the proposed OATC scheme considers the temporal reuse for spectral efficiency and the spatial reuse with transmit power control scheme for interference mitigation and capacity optimization. OATC scheme controls the transmit power to mitigate interference and optimizes the transmission capacity, which leads to the optimal achievable network capacity. We conduct the performance evaluation through numerical simulations and compare it with the existing FD MAC protocols. The numerical simulations reveal that considering only the concurrent transmissions in the FD system does not guarantee optimal transmission capacity. Moreover, the hybrid mechanism, including the sequential transmissions, is also crucial because of the interference problem. Besides, numerical simulation validates that the proposed OATC scheme accomplishes the optimal achievable network capacity with lower interference power and higher achievable throughput than the existing MAC protocols.

An Energy-Efficient Scheduling Algorithm With SIC and Power Control in WSNs

In large-scale wireless sensor networks (WSNs), spectrum efficiency and energy consumption are two challengeable problems to be solved due to the increasing traffic requirement and its limited energy. Successive interference cancellation (SIC) technology, which supports multiple parallel transmissions, gives an opportunity to improve the efficiency of data collection. However, those classical schemes suffer from high energy consumption, which presents a severe challenge to energy-constrained WSNs. To improve the transmission and energy efficiency of WSNs, we study an energy-efficient scheduling algorithm joint with SIC and power control in this paper. We first develop a non-uniform M-Level scheduling model to identify the beneficial opportunities and guarantee the transmission quality of SIC concurrency. Then, we formulate an energy efficiency maximization scheduling (EEMS) utility and further transform it into a combinatorial optimization problem. To reduce the computational complexity and obtain meaningful insights, two low-complexity optimization algorithms are proposed from the perspective of SIC scheduling and power control, respectively. Finally, extensive results demonstrate that the SIC scheduling design enables our proposed algorithm to achieve 51% higher throughput than the algorithm without SIC. Moreover, the energy efficiency of our proposed algorithm is improved by 37% compared with the existing algorithms, which indicates that our algorithm can search for the optimal configuration of SIC-concurrent transmissions and better manage the concurrent transmission power.

Differentiated Reception Modes Based Multiple Access

In recent years, the continuous increase in wireless data services and users’ traffic demand has been imposing great challenges on traditional multiple access control (MAC) methods. Some existing MAC techniques improve the communication system’s spectral efficiency (SE) via signal processing based cochannel interference (CCI) management. However, no interference management (IM) is free, i.e., its realization is based on the consumption of some communication resources, such as power and degree-of-freedom (DoF), which can also be used for the user’s desired data transmission. To lessen the resource cost for IM-based MAC, we exploit interactions among multiple wireless signals to propose a new MAC method, namely, Differentiated Reception Modes based Multiple Access (DRM-MA), in this paper. Under DRM-MA, a central control unit (CCU) is adopted to manage and pair multiple transmitting antennas with their serving receivers (Rxs). The CCU first calculates the phase difference of signals sent from each candidate antenna and perceived by the two receiving antennas of an Rx based on the locations of the transmitting antenna and Rx. Then, the CCU selects and pairs a proper transmitting antenna with each Rx, so that various Rxs can adopt either additive or subtractive reception mode to postprocess the signals received by its two antennas to realize in-phase desired signal construction and inverse-phase interference destruction. DRM-MA can avoid transmission performance loss incurred by signal processing-based IM. Our theoretical analysis and simulation results have shown that DRM-MA can enable concurrent data transmissions of multiple antenna-receiver pairs and output a high system’s SE.

Data concurrent transmission MAC protocol for application oriented underwater acoustic sensor networks

With the increasing demand for marine exploration, underwater acoustic sensor networks (UASNs) are prone to have the characteristics of large-scale, long term monitoring, and high data traffic load. Underwater media access control (MAC) protocols, which allow multiple users to share the common medium fairly and efficiently, are essential for the performance of UASNs. However, the design of MAC protocols is confronted with the challenges of spatial unfairness, data eruption, and low energy efficiency. In this paper, we propose a novel data concurrent transmission (DCT) MAC protocol, which is able to exploit long propagation delay and conduct concurrent transmission. Specifically, we present the theoretical performance analysis of the proposed MAC protocol in detail and give an analytical solution of the success concurrent transmission probability between nodes. In addition, simulation results are provided to demonstrate that our proposed protocol is appropriate for UASNs and can significantly improve the performance in terms of network throughput and energy consumption. Finally, we give some typical future applications of UASNs and discuss the demands on MAC protocol design.

BEV-SGD: Best Effort Voting SGD Against Byzantine Attacks for Analog-Aggregation-Based Federated Learning Over the Air

As a promising distributed learning technology, analog aggregation based federated learning over the air (FLOA) provides high communication efficiency and privacy provisioning under the edge computing paradigm. When all edge devices (workers) simultaneously upload their local updates to the parameter server (PS) through commonly shared time-frequency resources, the PS obtains the averaged update only rather than the individual local ones. While such a concurrent transmission and aggregation scheme reduces the latency and communication costs, it unfortunately renders FLOA vulnerable to Byzantine attacks. Aiming at Byzantine-resilient FLOA, this paper starts from analyzing the channel inversion (CI) mechanism that is widely used for power control in FLOA. Our theoretical analysis indicates that although CI can achieve good learning performance in the benign scenarios, it fails to work well with limited defensive capability against Byzantine attacks. Then, we propose a novel scheme called the best effort voting (BEV) power control policy that is integrated with stochastic gradient descent (SGD). Our BEV-SGD enhances the robustness of FLOA to Byzantine attacks, by allowing all the workers to send their local updates at their maximum transmit power. Under worst-case attacks, we derive the expected convergence rates of FLOA with CI and BEV power control policies, respectively. The rate comparison reveals that our BEV-SGD outperforms its counterpart with CI in terms of better convergence behavior, which is verified by experimental simulations.

Joint Resource Allocation on Slot, Space and Power Towards Concurrent Transmissions in UAV Ad Hoc Networks

With innovative applications of unmanned aerial vehicle (UAV) ad hoc networks in various areas, their demands on broad bandwidth, large capacity and low latency become prominent. The combination of millimeter wave, directional antenna and time division multiple access techniques, which enables concurrent transmissions, is promising to deal with it. In this paper, we study the resource allocation problem in UAV ad hoc networks. Specifically, the slot assignment, antenna boresight and transmit power are jointly optimized to promote the network capacity. First, we formulate the optimization problem as the maximization of the fairness-weighted network capacity, subject to the constraint on priority guarantee. Then, because the formulated problem is a mixed integer non-linear programming problem (MINLP), which is NP-hard, two algorithms called dual-based iterative search algorithm (DISA) and sequential exhausted allocation algorithm (SEAA) are respectively proposed to efficiently solve it with acceptable complexity. DISA slacks the MINLP into a continuous-variable optimization problem and solves it with the Lagrangian dual method in an iterative manner. As a heuristic method, SEAA schedules links sequentially, i.e., from high-priority to low-priority ones. Numerical results demonstrate that both DISA and SEAA can efficiently allocate resources for UAVs, while guaranteeing the fairness and priority of links.

A Dynamic Task Scheduling Strategy for Multi-Access Edge Computing in IRS-Aided Vehicular Networks

Multi-access Edge Computing (MEC) has played an important role in realizing intelligent beyond 5G (B5G) vehicular networks. The computation tasks of intelligent applications can be offloaded to and processed by near-end-user MEC servers to meet strict latency requirements. However, the latency of provided services is dependent on MEC processor scheduling and millimeter wave (mmWave) transmission conditions for the urban B5G vehicular networks. To alleviate the mmWave signal attenuation caused by buildings, Intelligent Reflecting Surface (IRS) has been regarded as efficient and prospective infrastructure. In this article, we study the IRS-aided MEC-served vehicular networks and analyze the relationship between computation resource allocation and offloading policy at an intersection. Considering the vehicle mobility patterns, transmission conditions, and task sizes, we optimize the task scheduling by improving the allocation of limited processors and IRS resource. Moreover, the mutual interference among concurrent transmissions is taken into account. Assuming the moving directions available, a dynamic task scheduling algorithm is proposed which considers both the communications and computations. The simulation results illustrate that our proposal outperforms benchmark methods in terms of task offloading rate, computing rate, and finish rate for the IRS-aided MEC-served vehicular networks.

Spinal stimulation for motor rehabilitation immediately modulates nociceptive transmission

Objective. Spinal cord injury (SCI) often results in debilitating movement impairments and neuropathic pain. Electrical stimulation of spinal neurons holds considerable promise both for enhancing neural transmission in weakened motor pathways and for reducing neural transmission in overactive nociceptive pathways. However, spinal stimulation paradigms currently under development for individuals living with SCI continue overwhelmingly to be developed in the context of motor rehabilitation alone. The objective of this study is to test the hypothesis that motor-targeted spinal stimulation simultaneously modulates spinal nociceptive transmission. Approach. We characterized the neuromodulatory actions of motor-targeted intraspinal microstimulation (ISMS) on the firing dynamics of large populations of discrete nociceptive specific and wide dynamic range (WDR) neurons. Neurons were accessed via dense microelectrode arrays implanted in vivo into lumbar enlargement of rats. Nociceptive and non-nociceptive cutaneous transmission was induced before, during, and after ISMS by mechanically probing the L5 dermatome. Main results. Our primary findings are that (a) sub-motor threshold ISMS delivered to spinal motor pools immediately modulates concurrent nociceptive transmission; (b) the magnitude of anti-nociceptive effects increases with longer durations of ISMS, including robust carryover effects; (c) the majority of all identified nociceptive-specific and WDR neurons exhibit firing rate reductions after only 10 min of ISMS; and (d) ISMS does not increase spinal responsiveness to non-nociceptive cutaneous transmission. These results lead to the conclusion that ISMS parameterized to enhance motor output results in an overall net decrease n spinal nociceptive transmission. Significance. These results suggest that ISMS may hold translational potential for neuropathic pain-related applications and that it may be uniquely suited to delivering multi-modal therapeutic benefits for individuals living with SCI.

Scanning Doppler LIDAR wind profiles to inform near shore atmospheric acoustic propagation modeling

This work presents a comprehensive experimental system to measure concurrent atmospheric acoustic transmission loss and meteorological conditions. A three-dimensional scanning Doppler lidar wind profiler captures real-time wind speed gradients at many locations along the acoustic propagation path of a simple pitch catch style study. A long-range acoustic device on an anchored pontoon sends known chirp sequences to a seven-channel receiver array at the water’s edge at ranges up to approximately one kilometer. Additional synchronized meteorological observations include temperature, humidity, and wind measured with anemometers. The meteorological data stream is used to inform the sound speed gradient implemented in a parabolic equation based numerical model of atmospheric acoustic propagation. The model can account for sea surface roughness and accommodate a sound speed profile that changes along the propagation range. Model predictions are compared to measured transmission losses. An assessment of the value of the computational cost of incorporating the varying sound speed profiles in the model is presented.