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Wenbo Fan

Publications and source records attributed to Wenbo Fan.

13 recordsLinked to original sources

Priority Random Access and Power Control for NOMA-ALOHA in Heterogeneous mMTC

This paper presents a novel priority random access (PRA) non-orthogonal multiple access assisted ALOHA, called PRA-NA, to provide access priority for machine-type devices (MTDs) with different delay requirements (i.e., delay-sensitive and delay-tolerant). We first introduce a received power level model that incorporates imperfect channel state information and imperfect successive interference cancellation to study the impact of practical non-ideal channel conditions. Two PRA strategies including fixed PRA-NA (FPRA-NA) and adaptive PRA-NA (APRA-NA) are then designed to reduce the average access delay of delay-sensitive MTDs in heterogeneous massive machine-type communications. Subsequently, the throughputs of both the FPRA-NA and APRA-NA strategies are analyzed to demonstrate their effectiveness. Moreover, to improve the energy efficiency of random access, we introduce an enhanced user barring algorithm (EUBA) to carry out power control. It is shown that our proposed EUBA can not only alleviate the user overload problem, but also reduce the average transmit power of MTDs. By extending it to the proposed PRA-NA schemes, we demonstrate via extensive simulation results that the random access performances in terms of throughput, access delay, and energy efficiency can be significantly improved over the conventional NOMA-ALOHA.

eess.SP

Optimal designs of heterogeneous grid transit networks

A general Continuum Approximation (CA) model is proposed for optimizing transit network designs (TND) in grid cities under spatially heterogeneous demand. While conventional studies often assume rigid geometric line configurations (e.g., unbranched orthogonal grids), our framework allows the grid bus lines to route more flexibly by making lateral movements and to form network configurations with line detouring, merging, and diverging. The resulting line and stop densities, as well as service headways, vary continuously across both directions of the city, constrained solely by vehicle flow conservation. By respecting non-uniform demand distributions, our heterogeneous networks substantially enlarge the class of heterogeneous network designs that can be represented and optimized within a tractable CA framework. To efficiently solve the optimization problem, we develop a sequential geometric programming framework that transforms the model into a sequence of standard geometric programming problems. Numerical experiments validate the accuracy of the proposed model and the solution method by comparing system metrics estimated by the CA models against the actual values computed from the discretized network designs. Under representative spatially heterogeneous demand scenarios, comparisons demonstrate that our model effectively reduces generalized costs by over 7% against existing homogeneous and restricted heterogeneous TND models. Key findings indicate that: (i) the proposed framework consistently outperforms these conventional counterparts across all tested scenarios; (ii) the fully heterogeneous structure becomes particularly advantageous when patron demand exhibits strong spatial heterogeneity; and (iii) these flexible designs yield the greatest benefits in high-demand, low-wage, and large-area cities.

physics.app-ph

One-hot Coding-based URA with RFFI-Enabled Message Authentication

Unsourced random access (URA) has emerged as a promising paradigm for enabling massive connectivity in Internet-of-Things (IoT) networks. However, since URA transmissions do not contain device identifiers, the receiver may not associate decoded messages with their originating devices, introducing a security vulnerability: forged messages may be decoded as legitimate. To address this problem, this paper proposes a one-hot coding (OHC)-based URA framework that enables message authentication while preserving the unsourced transmission principle. Specifically, distinct messages are mapped onto orthogonal channel uses via an OHC-based common codebook and transmitted using on-off keying modulation. The resulting orthogonal channel structure enables radio-frequency fingerprint identification to authenticate received signals by exploiting device-specific hardware impairments, thereby authenticating decoded messages without introducing an additional authentication payload. Analytical expressions for the per-user probability of error and the probability of successful spoofing are derived. Numerical results demonstrate that the proposed scheme enables secure URA transmission while maintaining reliable communication performance in ultra-short-payload IoT scenarios.

eess.SP

Approximation Models for Shared Mobility Rebalancing Under Structured Spatial Imbalance

Shared mobility systems (e.g., shared cars and ride-hailing services) generate persistent spatial imbalances as vehicles concentrate at popular destinations, leaving trip origins depleted of supply. Operators incur substantial costs in repositioning empty vehicles, and quantifying the theoretical minimum rebalancing distance is practically important. Exact computation requires solving a transportation linear program that is challenging at the city scale. Closed-form approximation models are derived for the minimum rebalancing distance in rectangular service regions. Parallel derivations are presented for the Manhattan metric (grid road networks) and the Euclidean metric (unconstrained movement). A scalar spatial imbalance index condenses the full demand pattern into a single interpretable quantity. Both models share a unified structure: the per-vehicle rebalancing distance scales with the square root of service area, the imbalance index, and a shape factor that depends solely on the aspect ratio. Calibration and validation against 500 exact LP solutions per metric confirm the area-scaling exponent to within 2\% of the theoretical prediction, across three demand distribution families. An empirical case study using January 2026 New York City for-hire vehicle trip data across 263 traffic analysis zones confirms that the formula generalizes to real-world, network-constrained demand. The results equip operators and system designers with solver-free, theoretically grounded tools for benchmarking rebalancing performance and optimizing service, rebalancing frequency, and demand-management interventions.

physics.app-ph

Design of Transit Networks: Global Optimization of Continuous Approximation Models via Geometric Programming

Continuous approximation (CA) models have been widely adopted in transit network design studies due to their strong analytical tractability and high computational efficiency. However, such models are typically formulated as nonconvex optimization problems, and existing solution approaches mainly rely on iterative algorithms that exploit first-order optimality information or nonlinear programming solvers, whose solution quality lacks stability guarantees under complex demand conditions. This paper proposes a geometric programming (GP)-based CA method for transit network design, which can be efficiently solved to global optimality. Numerical experiments are conducted on both homogeneous and heterogeneous network settings to evaluate the effectiveness of the proposed approach. Comprehensive tests are performed under the combinations of six heterogeneous demand distributions, four levels of total passenger demand, and three value-of-time parameters. The results indicate that the GP approach consistently outperforms the coordinate descent method across all test cases, achieving cost reductions of approximately 1%-4%, even when the latter converges to identical solutions under different initializations. In comparison, nonlinear programming solvers, with fmincon as a representative example, are able to obtain globally optimal solutions comparable to those of the GP approach in low-demand heterogeneous networks; however, their performance becomes unstable under high-demand conditions. These findings demonstrate that GP provides an efficient and robust optimization framework for solving CA-based transit network design problems, especially in high-demand and highly heterogeneous network environments.

math.OC

Investigation of the Physical Mechanism behind Retention Loss in FeFETs with MIFIFIS Gate Structure

A Metal-Gate Blocking Layer (GBL)- Ferroelectric-Tunnel Dielectric Layer (TDL)-Ferroelectric -Channel Insulator (Ch.IL)-Si (MIFIFIS) structure is proposed to achieve a larger MW for applications in Fe-NAND. However, the large retention loss (RL) in the MIFIFIS structure restricts its application. In this work, we vary the physical thickness of the GBL and TDL, and conduct an in-depth analysis of the energy bands of the gate structure to investigate the physical mechanism behind the RL in FeFETs with the MIFIFIS structure. The physical origin of the RL is that the electric field direction across the TDL reduces the potential barrier provided by the ferroelectric near the silicon substrate. Based on the above physical mechanism, the RL can be reduced to 12% and 0.2% by redesigning the gate structure or reducing the pulse amplitude, respectively. Our work contributes to a deeper understanding of the physical mechanism behind the RL in FeFETs with the MIFIFIS gate structure. It provides guidance for enhancing the reliability of FeFETs.

physics.app-ph

Fly-by transit: A novel door-to-door shared mobility with minimal stops

This paper introduces fly-by transit (FBT), a novel mobility system that employs modular mini-electric vehicles (mini-EVs) to provide door-to-door shared mobility with minimal stops. Unlike existing modular minibus concepts that rely on in-motion coupling and passenger transfers -- technologies unlikely to mature soon -- FBT lowers the technological barriers by building upon near-term feasible solutions. The system comprises two complementary mini-EV modules: low-cost trailers for on-demand feeder trips and high-performance leaders that guide coupled trailers in high-speed platoons along trunk lines. Trailers operate independently for detour-free feeder services, while stationary coupling at designated hubs enables platoons to achieve economies of scale (EoS). In-motion decoupling of the tail trailer allows stop-less operation without delaying the main convoy. As a proof of concept, a stylized corridor model is developed to analyze optimal FBT design. Results indicate that FBT can substantially reduce travel times relative to conventional buses and lower operating costs compared with e-hailing taxis. Numerical analyses further demonstrate that FBT achieves stronger EoS than both buses and taxis, yielding more than 13\% savings in generalized system costs. By addressing key limitations of existing transit systems, this study establishes FBT as a practical and scalable pathway toward transformative urban mobility and outlines directions for future research.

physics.app-ph

Novel operational algorithms for ride-pooling as on-demand feeder services

Ride-pooling (RP) service, as a form of shared mobility, enables multiple riders with similar itineraries to share the same vehicle and split the fee. This makes RP a promising on-demand feeder service for patrons with a common trip end in urban transportation. We propose the RP as Feeder (RPaF) services with tailored operational algorithms. Specifically, we have developed (i) a batch-based matching algorithm that pools a batch of requests within an optimized buffer distance to each RP vehicle; (ii) a dispatching algorithm that adaptively dispatches vehicles to pick up the matched requests for certain occupancy target; and (iii) a repositioning algorithm that relocates vehicles to unmatched requests based on their level of urgency. An agent-based microscopic simulation platform is designed to execute these operational algorithms (via the Operator module), generate spatially distributed random requests (Patron module), and account for traffic conditions (Vehicle module) in street networks. Extensive numerical experiments are conducted to showcase the effectiveness of RPaF services across various demand scenarios in typical morning rush hours. We compare RFaF with two on-demand feeder counterparts proposed in previous studies: Ride-Sharing as Feeder (RSaF) and Flexible-Route Feeder-Bus Transit (Flex-FBT). Comparisons reveal that given the same fleet size, RPaF generally outperforms RSaF in higher service rates (i.e., the percentage of requests served over all requests) and Flex-FBT in shorter average trip times for patrons. Lastly, we illustrate the implementation of RPaF in a real-world case study of the uptown Manhattan network (USA) using actual taxi trip data. The results demonstrate that RPaF effectively balances the level of service (service rate and patrons' average trip time) with operational costs (fleet size).

cs.NI

Optimal design of ride-pooling as on-demand feeder services

The technology-enabled ride-pooling (RP) is designed as an on-demand feeder service to connect remote areas to transit terminals (or activity centers). We propose the so-called ``hold-dispatch'' operation strategy, which imposes a target number of shared rides (termed the ride-pooling size) for each vehicle to enhance RP's transportation efficiency. Analytical models are formulated at the planning level to estimate the costs of the RP operator and the patrons. Accordingly, the design problem is constructed to minimize the total system cost concerning the system layout (i.e., in terms of service zone partitioning), resource deployment (i.e., fleet size), and operational decision (i.e., ride-pooling size). The proposed models admit spatial heterogeneity arising from the non-uniformity of demand distributions and service locations, and can furnish heterogeneous designs. Closed-form formulas for the optimal zoning and fleet size are developed, which unveil fundamental insights regarding the impacts of key operating factors (e.g., demand density and distance to the terminal). Extensive numerical experiments demonstrate (i) the effectiveness of heterogeneous service designs and (ii) the advantage of the proposed RP service with hold-dispatch strategy over alternative designs studied in the literature, i.e., RP with a ``quick-dispatch'' strategy and flexible-route transit, in a wide range of operating scenarios. These findings can assist transportation network companies and transit agencies in successfully integrating RP and transit services.

physics.soc-ph

Macroscopic fundamental diagram with volume-delay relationship: model derivation, empirical validation and invariance property

This paper presents a macroscopic fundamental diagram model with volume-delay relationship (MFD-VD) for road traffic networks, by exploring two new data sources: license plate cameras (LPCs) and road congestion indices (RCIs). We derive a first-order, nonlinear and implicit ordinary differential equation involving the network accumulation (the {\it volume}) and average congestion index (the {\it delay}), and use empirical data from a 266 km$^2$ urban network to fit an accumulation-based MFD with $R^2>0.9$. The issue of incomplete traffic volume observed by the LPCs is addressed with a theoretical derivation of the observability-invariant property: The ratio of traffic volume to the critical value (corresponding to the peak of the MFD) is independent of the (unknown) proportion of those detected vehicles. Conditions for such a property to hold are discussed in theory and verified empirically. This offers a practical way to estimate the ratio-to-critical-value, which is an important indicator of network saturation and efficiency, by simply working with a finite set of LPCs. The significance of our work is the introduction of two new data sources widely available to study empirical MFDs, as well as the removal of the assumptions of full observability, known detection rates, and spatially uniform sensors, which are typically required in conventional approaches based on loop detector and floating car data.

physics.soc-ph

Revisit the scheduling problem in Hurdle, V.F., 1973: A novel mathematical solution approach and two extensions

The scheduling problem in Hurdle (1973) was formulated in a general form that simultaneously concerned the vehicle dispatching, circulating, fleet sizing, and patron queueing. As a constrained variational problem, it remains not fully solved for decades. With technical prowess in graphic analysis, the author unveiled the closed-form solution for the optimal dispatch rates (with key variables undetermined though), but only suggested the lower and upper bounds of the optimal fleet size. Additionally, such a graphic analysis method lacks high efficiency in computing specific scheduling problems, which are often of a large scale (e.g., hundreds of bus lines). In light of this, the paper proposes a novel mathematical solution approach that first relaxes the original problem to an unconstrained one, and then attacks it using calculus of variations. The corresponding Euler-Lagrange equation yields the closed-form solution of the optimal dispatching rates, to which Hurdle's results are a special case. Thanks to the proposed approach, the optimal fleet size can also be solved. This paper completes the work of Hurdle (1973) by formalizing a solution method and generalizing the results. Based on that, we further make two extensions to the scheduling problem of general bus lines with multiple origins and destinations and that of mixed-size or modular buses. Closed-form results are also obtained with new insights. Among others, we find that the solutions for shuttle/feeder lines are a special case to our results of general bus lines. Numerical examples are also provided to demonstrate the effectiveness and efficiency of the proposed approach.

math.OC

Planning Skip-Stop Transit Service under Heterogeneous Demands

Transit vehicles operating under skip-stop service visit only a subset of the stops residing along a corridor. It is a strategy commonly used to increase vehicle speeds and reduce patron travel times. The present paper develops a continuous approximation model to optimally design a select form of skip-stop service, termed AB-type service. The model accounts for spatially-heterogeneous demand patterns. An efficient heuristic is developed to obtain solutions. These are shown to be near-optimal for a variety of numerical examples. Results also indicate that optimal AB-type designs outperform optimized all-stop service in a variety of cases. The AB-type service is found to be especially competitive when travel demands are high, trip origins are unevenly distributed along a corridor, and patrons have relatively high values of time. In these cases, AB-type service is found to reduce system costs by as much as 8%.

math.OC

Traffic dynamics and optimal control in a city served by ride-sourcing vehicles

This paper presents an interactive bathtub model for describing the traffic dynamics of ride-sourcing vehicles including non-shared taxis and ride-pooling cars. A city with a network of undifferentiated streets and solely served by ride-sourcing services is assumed to facilitate the modeling, isolate the congestion contribution, and accordingly develop control strategies. The proposed model is parsimonious with only input information of the total lane length of the network, the in-flux of demand, and the travel distance distributions. The output of the model, however, captures not only the traffic dynamics of vehicles but also the dynamic states of passengers in ride-pooling services in terms of the total number, the remaining travel distances, and the queue of unmatched requests at any system time. Useful system metrics can be exploited for use of the authorities to monitor, predict, and control the traffic, as well as for the TNCs to determine the fleet sizes, dispatch vehicles, and measure the service productivity. For illustration, we propose a robust control rule to manage the traffic efficiently and avoid gridlock, and also present time-varying ride-pooling sizes to eliminate the queue of unmatched requests. Numerical examples demonstrate the effectiveness of the proposed model and the control and operation strategies.

math.OC