Siyu Lin

Reconfiguration-Assisted Charging in Large-Scale Lithium-Ion Battery Systems

Large-scale lithium-ion battery packs are widely adopted in systems such as electric vehicles and energy backup in power grids. Due to factors such as manufacturing difference and heterogeneous discharging conditions, cells in the battery pack may have different statuses, such as diverse voltage levels. This cell diversity is commonly known as the cell imbalance issue. For the charging of battery packs, the cell imbalance not only early on terminates the charging process before all cells are fully charged, but also leads to different desired charging currents among cells. In this paper, based on the advancement in reconfigurable battery systems, we demonstrate how to utilize system reconfigurability to mitigate the impact of cell imbalance on an efficient charging process. With the proposed reconfiguration-assisted charging (RAC), cells in the system are categorized according to their real-time voltages, and the charging process is performed in a category-by-category manner. To charge cells in a given category, a graph-based algorithm is presented to charge cells with their desired charging currents, respectively. We evaluate RAC through both experiments and simulations. The results demonstrate that the RAC increases the capacity charged into cells by about 25% and yields a dramatically reduced variance.

Finite-state Markov channel modeling for vehicle-to-infrastructure communications

Accurate and mathematically tractable channel models are valuable tools in the network performance analysis and simulation. Most of Markov chain channel models are designed based on first-order Markov chain, which means that each channel state can only transit to the adjacent states. However, this assumption is no longer valid when the transceivers operate in high mobility scenarios, such as high speed vehicle communications. The fast time-varying characteristic of channel cannot be described by first-order Markov chain accurately. In this paper, we propose a novel finite-state Markov chain (FSMC) channel model for vehicle-to-infrastructure communications considering the fast time-varying fading with high mobility. The accurate closed form expressions of state transition probabilities between any two channel states are derived. The accuracy of the proposed Markov channel model is validated by the extensive simulation results. Furthermore, the effects of vehicle speed on state transition probabilities are discussed.

A TDL Based Non-WSSUS Vehicle-to-Vehicle Channel Model

This paper proposes a non-wide-sense-stationary-uncorrelated scattering (WSSUS) channel model for vehicle-to-vehicle (V2V) communication systems. The proposed channel model is based on the tapped-delay line (TDL) structure and considers the correlation between taps both in amplitude and phase. Using the relationship between the correlation coefficients of complex Gaussian, Weibull, and Uniform random variables (RVs), the amplitude and the phase of taps with different delays are modeled as correlated RVs to reflect the non-WSSUS properties of V2V channels. The effectiveness of the proposed channel model and simulation method is validated by the measurements in different scenarios.

Transmission Interference Improvement of Railway Communication via Distributed Antennas System

Transmission interference is a key performance indicator of railway digital mobile communication system(RDMCS), whose performance will become worse in high-speed railway. The factors that influence the transmission interference of RDMCS are analyzed. Based on the relationship between speed and transmission interference, the scheme based on distributed antennas system (DAS) is proposed to improve transmission interference of RDMCS. The proposed scheme can reduce the collision probability between data transmission and handover with the improved performance of transmission interference. Effectiveness of the proposed scheme is verified by simulations and theoretical analysis.

RAC: Reconfiguration-Assisted Charging in Large-Scale Lithium-Ion Battery Systems

Large-scale lithium-ion battery packs are widely adopted in systems such as electric vehicles and energy backup in power grids. Due to factors such as manufacturing difference and heterogeneous discharging conditions, cells in the battery pack may have different statuses, such as diverse voltage levels. This cell diversity is commonly known as the cell imbalance issue. For the charging of battery packs, the cell imbalance not only early on terminates the charging process before all cells are fully charged, but also leads to different desired charging currents among cells. In this paper, based on the advancement in reconfigurable battery systems, we demonstrate how to utilize system reconfigurability to mitigate the impact of cell imbalance on an efficient charging process. With the proposed reconfiguration-assisted charging (RAC), cells in the system are categorized according to their real-time voltages, and the charging process is performed in a category-by-category manner. To charge cells in a given category, a graph-based algorithm is presented to charge cells with their desired charging currents, respectively. We evaluate RAC through both experiments and simulations. The results demonstrate that the RAC increases the capacity charged into cells by about 25% and yields a dramatically reduced variance.

Adaptive Barrier Coverage Using Software Defined Sensor Networks

This paper investigates the adaptive barrier coverage system in wireless sensor networks, where multiple mobile sensor nodes collaboratively move based on cloud computing. This system aims to adaptively maintain a barrier coverage surrounding a dynamic zone, such as nuclear leakage area and toxic gas area. Since such a zone is usually dangerous and invisible, it is necessary to monitor and track its boundary for detecting unwanted people nearby and warning them. Existing studies on mobile barrier coverage mainly focus on static zones, which cannot directly apply into dynamic zones because their movement strategies are not flexible with dynamics. To address such a problem, we propose a novel adaptive barrier coverage system. The challenge is to effectively maintain the barrier when the change of dynamic zone is unpredictable. The proposed system leverages the software defined concept, in which the mobile sensor nodes execute the local sensing tasks and the cloud computes the real-time optimal strategy to control the movements of nodes. Extensive simulations based on large-scale real trace demonstrate the efficiency and the efficacy of the proposed system.

Advanced Dynamic Channel Access Strategy in Spectrum Sharing 5G Systems

5G wireless communications aim at providing higher data rates, spectral efficiency, and energy efficiency than 4G. To achieve this target, the spectrum resource with low utilization is emptied out for 5G refarming. The refarmed spectrum is of effective propagation nature; however, it leads to extensive competition between PTOs and DTOs. To mitigate such competition, dynamic spectrum sharing should be realized. For this purpose, a spectrum sharing framework of a 5G system is designed in this article, in which the public users and dedicated users can access the sharing spectrum dynamically. In the framework, to ensure the QoE of the secondary users in a spectrum sharing system, the DTO in this case, an advanced dynamic channel access strategy is proposed. The spectrum sharing system states are modeled as a finite state Markov chain, and are used to analyze the system state transition model. Based on the analysis results, the optimal dynamic channel access strategy with minimum queuing time for DTO is derived by a Markov decision process. Extensive simulations show that the proposed dynamic channel access strategy can achieve the optimal queuing time.

Design and Test of a High QoS Radio Network for CBTC Systems in Subway Tunnels

Communications Based Train Control Systems require high quality radio data communications for train signaling and control. Actually most of these systems use 2.4GHz band with proprietary radio transceivers and leaky feeder as distribution system. All them demand a high QoS radio network to improve the efficiency of railway networks. We present narrow band, broad band and data correlated measurements taken in Madrid underground with a transmission system at 2.4 GHz in a test network of 2 km length in subway tunnels. The architecture proposed has a strong overlap in between cells to improve reliability and QoS. The radio planning of the network is carefully described and modeled with narrow band and broadband measurements and statistics. The result is a network with 99.7% of packets transmitted correctly and average propagation delay of 20ms. These results fulfill the specifications QoS of CBTC systems.

Cluster-Based Nonstationary Channel Modeling for Vehicle-to-Vehicle Communications

In this letter, a three-dimensional (3-D) cluster-based nonstationary channel model is proposed for vehicle-to-vehicle (V2V) communications. To efficiently describe the scattering environment and reflect the nonstationarity of V2V channels, the proposed model considers the single- and double-bounced clusters in 3-D space, and includes the effect of activity of clusters by introducing visibility regions. Furthermore, based on the geometrical relationships in the model, the channel impulse response is derived as a sum of the line-of-sight, single- and double-bounced rays, and the space-time-frequency correlation properties are analyzed. Finally, the accuracy of the proposed model is validated by realistic V2V channel measurements.

Robust QoS-Aware Cross-layer Design of Adaptive Modulation Transmission on OFDM Systems in High-Speed Railway

In this paper, we consider an orthogonal frequency division multiplexing communication system that adopts frame-by-frame transmission in high-speed railway (HSR) scenario. Due to the increase in demand for the QoS sensitive services, an efficient QoS-aware transmission strategy that improves the system performance is required urgently. Many efforts have been devoted to addressing this problem with the assumption of block fading channel in a frame duration. However, due to the frequent channel quality variation in a frame duration and serious inter channel interference in HSR scenario, the throughput of the QoS sensitive services degrades severely. Hence, a robust cross-layer transmission strategy that combines adaptive modulation (AM) scheme with truncated automatic repeat request protocol is proposed. In this cross-layer formulation, the normalized average throughput is optimized subject to the average power and the packet loss rate (PLR) requirements. First, we derive the closed form average bit error rate that represents the PLR requirement at the physical layer. Second, we obtain the solution of robust AM scheme and power allocation policy in the case of continuous rate. Third, we present the adaptive bits and power allocation scheme in the case of discrete rate, which can be implemented in practice. Finally, the performance of the proposed transmission strategy is evaluated by extensive simulations. Comparing with the constant transmit power AM scheme, the throughput increases by 20%, which demonstrates that the proposed robust cross-layer design is suitable for the HSR communication systems.