IEEE Vehicular technology 2016 Title and Abstract

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY TOPICS 2016
Impact of General Channel Aging Conditions on the Downlink Performance of Massive
MIMO
Abstract - Recent works have identified massive multiple-inputmultiple- output (MIMO) as a
key technology for achieving substantial gains in spectral and energy efficiency. Additionally,
the turn to low-cost transceivers, being prone to hardware impairments is the most effective and
attractive way for costefficient applications concerning massive MIMO systems. In this context,
the impact of channel aging, which severely affects the performance, is investigated herein by
considering a generalized model. Specifically, we show that both Doppler shift because of the
users’ relative movement as well as phase noise due to noisy local oscillators (LOs) contribute to
channel aging. To this end, we first propose a joint model, encompassing both effects, in order to
investigate the performance of a massive MIMO system based on the inevitable time-varying
nature of realistic mobile communications. Then, we derive the deterministic equivalents (DEs)
for the signal-to-noise-and-interference ratios (SINRs) with maximum ratio transmission (MRT)
and regularized zero-forcing precoding (RZF). Our analysis not only demonstrates a performance
comparison between MRT and RZF under these conditions, but most importantly, it reveals
interesting properties regarding the effects of user mobility and phase noise. In particular, the
large antenna limit behavior depends profoundly on both effects, but the burden due to user
mobility is much more detrimental than phase noise even for moderate user velocities ( 30 km/h),
while the negative impact of phase noise is noteworthy at lower mobility conditions. Moreover,
massive MIMO systems are favorable even in general channel aging conditions. Nevertheless,
we demonstrate that the transmit power of each user to maintain a certain quality of service can
be scaled down at most by 1pM (M is the number of BS antennas), which indicates that the joint
effects of phase noise and user mobility do not degrade the power scaling law, but only the
achievable sum-ra- e.
IEEE Transactions on Vehicular Technology (May 2016)
Quality-Oriented Rate Control and Resource Allocation in Time-Varying
OFDMANetworks

Abstract - In this paper, we propose a resource-management scheme for on-demand video
streaming in orthogonal frequencydivision multiple access (OFDMA) networks with both
timevarying channels and a user’s personalized quality requirement. We design a user quality-
satisfaction model to evaluate the degree of the user quality satisfaction with respect to his/her
personalized quality requirement. We propose a joint rate control associated with the quality
adjustment at the application layer, and resource allocation associated with the power allocation
and subcarrier assignment at the physical layer to perform the dynamic resource management.
By using the Lyapunov optimization technique, we develop a joint rate control and resource
allocation (JRCRA) algorithm to maximize the time-averaged quality satisfaction of all users
(QSAU). We show that the QSAU achieved by the JRCRA algorithm without any prior
knowledge of the channel statistics can arbitrarily attain the optimal QSAU achieved by the
algorithm with a complete knowledge of the channel statistics. Simulation results verify the
advantages of the proposed JRCRA algorithm.
IEEE Transactions on Vehicular Technology (June 2016)
Optimal Content Prefetching in NDN Vehicle-to-Infrastructure Scenario
Abstract - Data replication and in-network storage are two basic principles of the Information
Centric Networking (ICN) framework in which caches spread out in the network can be used to
store the most popular contents. This work shows how one of the ICN architectures, the Named
Data Networking (NDN), with content pre-fetching can maximize the probability that a user
retrieves the desired content in a Vehicle-to-Infrastructure scenario. We give an ILP formulation
of the problem of optimally distributing content in the network nodes while accounting for the
available storage capacity and the available link capacity. The optimization framework is then
leveraged to evaluate the impact on content retrievability of topology- and network-related
parameters as the number and mobility models of moving users, the size of the content catalog
and the location of the available caches. Moreover, we show how the proposed model can be
modified to find the minimum storage occupancy to achieve a given content retrievability level.
The results obtained from the optimization model are finally validated against a Name Data
Networking architecture through simulations in ndnSIM.

Distance-based Ecological Driving Scheme using a Two-stage Hierarchy for Long-term
Optimization and Short-term Adaptation
Abstract - This paper proposes a distance-based ecological (eco) driving scheme with two
stages: one for long-term speed optimization and the other for short-term adaptation to actual
traffic conditions. Before departure, the speed profile for an entire route is optimized in a
distance domain by using characteristics of the drivetrain and road conditions. Then, while
driving, the speed at only the next location is controlled to follow the optimal speed profile and
adapt it for traffic conditions, which allows for real-time adaptation, maintaining optimal driving
in the long term. In order to localize the change of the optimal speed profile due to traffic
conditions, models for fuel rate of a conventional vehicle and vehicle propulsion systems were
formulated in a distance domain, and a distance-based optimal speed profile was generated. The
proposed eco-driving scheme is optimized by the quadratic programming method, and its
validity is tested by simulation.
Fair Congestion Control in Vehicular Networks With Beaconing Rate Adaptation at
Multiple Transmit Powers
Abstract - Cooperative intervehicular applications rely on the exchange of broadcast single-hop
status messages among vehicles, which are called beacons. The aggregated load on the wireless
channel due to periodic beacons can prevent the transmission of other types of messages, which
is called channel congestion due to beaconing activity. In this paper, we propose to let vehicles
transmit with different transmit power levels, each with a particular beaconing rate. The selection
of the rate is modeled as a network utility maximization (NUM) problem. Our goal is to
maximize the number of beacons delivered at each transmit power according to a well-defined
fairness notion while complying with the maximum allowed beaconing load on the channel. The
algorithm parameters can be set per vehicle and dynamically changed, which provides enough
flexibility to support multiple applications on top of the control scheme, whereas the NUM
model provides a rigorous framework to design a broad family of simple and decentralized
algorithms, with proved convergence guarantees to a fair allocation solution. Simulation results

validate our approach and show that it provides fair rate allocations in realistic multihop and
dynamic scenarios with packet losses.
Traffic-Aware Cell Management for Green Ultra-dense Small Cell Networks
Abstract - To reduce the power consumption of 5G ultradense small cell networks, base stations
can be switched to low power sleep modes when local traffic levels are low. In this paper, a
novel sleep mode control algorithm is proposed to control such sleep modes. The algorithm
innovates a concept called Traffic-Aware Cell Management (TACM). It involves cell division,
cell death and cell migration to represent adaptations of networks, where state transitions of base
stations are controlled. Direction of arrival is adopted for distributed decision making. The
TACM algorithm aims at reducing the network power consumption while alleviating the impacts
of applying sleep modes, such as mitigating system overheads and reducing user transmission
power. The TACM algorithm is compared with a recent consolidated baseline scheme by
simulation on networks with unbalanced traffic distributions and with base stations at random
locations. In contrast, the TACM algorithm shows a significant improvement in mitigating
system overheads due to no load information exchange overhead and up to 72 times less
switching frequency. Up to 81% network power consumption can be reduced compared with the
baseline scheme if considering high energy consumption of switching transient states. In
addition, at a low traffic level, average uplink transmission power is reduced by 79%
comparatively. Furthermore, the impact of important performance governing parameters of the
TACM algorithm is analysed. The insensitivity to the estimation accuracy of direction of arrival
is also demonstrated. The results show that the proposed TACM algorithm has a comprehensive
advantage of power reduction and overhead mitigation over the baseline scheme.
Analytical Model and Performance evaluation of Long Term Evolution for vehicle Safety
Services
Abstract - In traffic jam or dense vehicle environment, vehicular ad-hoc networks (VANET)
can’t meet safety requirement due to serious packet collision. The traditional cellular network
solves packet collision, but suffers from long end-to-end delay. 3GPP Long Term Evolution

(LTE) overcomes both drawbacks, thus it may be used instead of VANET in some extreme
environments. We use Markov models with the dynamic scheduling and semipersistent
scheduling (SPS) to evaluate how many idle resources of LTE can be provided for safety
services and how safety applications impact on LTE traditional users. Based on the analysis, we
propose to reserve the idle radio resources in LTE for vehicular safety services (LTE-V).
Additionally, we propose the weighted-fair-queueing (WFQ) algorithm to schedule beacons for
safety services using LTE reserved resource. Numerical results verify that the proposed
mechanism can significantly improve the reliability of safety application by borrowing limited
LTE bandwidth. We also build NS3 simulation platform to verify the effectiveness of the
proposed Markov models. Finally, the reliability of applications including cooperation collision
warning, slow vehicle indication and rear-end collision warning using DSRC with LTE-V are
evaluated. The simulation results demonstrate that the stringent QoS requirement of the above
three applications can be satisfied even under heavy traffic.
Shortest Link Scheduling Algorithms in Wireless Networks Under SINR
Abstract - This paper considers the shortest link scheduling (SLS) problem in wireless networks
under the Signalto-Interference-plus-Noise-Ratio (SINR) model. We propose an
$O(log(l_{max}/l_{min}))$ approximation algorithm SLSPC (Shortest Link Scheduling with
Power Control) with oblivious power assignment and an $O(log_{1+varphi}(l_{max}/l_{min})$
approximation algorithm SLSUM (Shortest Link Scheduling with Uniform or Mean power
assignment) with uniform or mean power control, where $varphi>$ 0 is a constant serving as a
regulatory factor for slight transmit power adjustment, and $_{max}$ and $_{min}$ denote the
lengths of the longest and the shortest links, respectively. We conduct rigorous theoretical
performance analysis to analyze the feasibility and approximation factors of the proposed
algorithms. We also carry out an extensive comparison-based simulation study, whose results
indicate that the performances of SLSPC and SLSUM are superior over the state-of-the-art as the
set of the so-called “black and gray” links, which are difficult to schedule and should be
scheduled sequentially, are completely removed by adjusting the transmit power appropriately

via $varphi$ . Our numerical analysis demonstrates that the approximation ratios of our
algorithms are tighter than the best known ones.
Simultaneous Vehicle Real-time Longitudinal and Lateral Velocity Estimation
Abstract - Accurate information about vehicle longitudinal and lateral velocities is vital for
efficient operation of many vehicle control systems. In this paper, an estimation structure to
simultaneously estimate vehicle velocities in longitudinal and lateral directions is developed and
experimentally validated. This structure includes two parallel estimators: the first estimator is a
kinematic-based observer for longitudinal velocity estimation, and the second is a combination
of a kinematic-based observer and an inverse tire model to estimate vehicle lateral velocity. The
proposed structure can effectively handle the additive biases, which are common in vehicle’s
stock accelerometers’ signals, and provide accurate estimate of vehicle velocities when one (or
more than one) wheel experiences the excessive slippage. Additionally, the proposed structure is
not sensitive to changes in parameters of tire model and vehicle mass. The performance of this
estimation structure is validated by experimental studies.
Symbol Misalignment Estimation in Asynchronous Physical-Layer Network Coding
Abstract - Symbol misalignment is inevitable in asynchronous physical-layer network coding
(PNC) systems. It is paramount that such symbol misalignment is taken into account in PNC
decoding for good performance. Thus, accurate estimation of symbol misalignment is crucial.
This paper argues that, when Nyquist pulses (i.e., ISI-free pulses) are adopted, signal samples
only need to be collected at baud rate for optimal symbol misalignment estimation. Based on this
principle, we propose a highly accurate symbol misalignment estimation method with low
complexity. Our method makes use of the constant amplitude zero autocorrelation sequence
(Zadoff-Chu sequence). We derive a maximum-likelihood (ML) estimator for symbol
misalignment based on the cross-correlation result of the Zadoff-Chu sequence. Unlike previous
methods that employ oversampling, our estimation method only requires baud-rate sampling,
thus has much lower complexity. Extensive simulations show that our method can accurately
estimate both integral and fractional symbol misalignments using sinc and raised cosine pulses.

The root mean square error of the estimation is below 10�2 (in unit of symbol duration) when
SNR is above 15 dB, 18 dB, and 21 dB for 127-, 63-, and 31-bit length Zadoff-Chu sequences,
respectively. Furthermore, our method, being an ML estimation method, has no error floor in the
high-SNR regime, whereas the prior methods exhibit an error floor.
Frequency-Domain In-Vehicle UWB Channel Modeling
Abstract - This paper aims to present a simple but robust model characterizing the frequency-
dependent transfer function of an in-vehicle ultrawideband (UWB) channel. A large number of
transfer functions spanning the UWB (3–11 GHz) are recorded inside the passenger
compartment of a four-seated sedan. It is found that the complex transfer function can be
decomposed into two terms, the first term being a real-valued long-term trend that characterizes
frequency dependence with a power law and the second term forming a complex correlative
discrete series that may be represented via an autoregressive (AR) model. An exhaustive
simulation framework is laid out based on empirical equations characterizing trend parameters
and AR process coefficients. The simulation of the transfer function is straightforward as it
involves only a handful of variables; however, it is in good agreement with the actual measured
data. The proposed model is further validated by comparing different channel parameters, such
as coherence bandwidth, power delay profile, and root-mean-square delay spread, obtained from
raw and synthetic data sets. It is also shown how the model can be compared with existing time-
domain Saleh–Valenzuela-influenced models and related IEEE standards.
Time-domain N-continuous OFDM: System Architecture and Performance Analysis
Abstract - N-continuous orthogonal frequency division multiplexing (NC-OFDM) is a
promising technique to achieve significant sidelobe suppression for baseband OFDM signals.
However, NC-OFDM usually has high implementation complexity which limits its practical
applications. Based on conventional NCOFDM, this paper proposes a new technique, termed
timedomain N-continuous OFDM (TD-NC-OFDM), which shifts the processing burden from the
frequency domain to the time domain. This is achieved through adding a smooth signal, which is
linearly combined by rectangularly pulsed OFDM basis signals consisting of a novel basis set.

We prove that TD-NC-OFDM with the basis set is essentially equivalent to conventional NC-
OFDM. Furthermore, using the time-domain structure, an asymptotic spectrum analysis of N-
continuous OFDM signals is obtained by developing a closed-form expression related to sidelobe
decaying. This paper also examines the impact of TD-NC-OFDM on the received signal-to-
interference-plus-noise ratio (SINR), and derives closed-form expressions.
Multiple-Model Switching Control of Vehicle Longitudinal Dynamics for Platoon-Level
Automation
Abstract - Platooning of autonomous vehicles has the potential to significantly benefit road
traffic. This paper presents a new robust acceleration tracking control of vehicle longitudinal
dynamics toward platoon-level automation. Based on a multiple-model switching structure, this
design divides the large uncertainties of vehicle dynamics into small uncertainties and,
accordingly, develops multiple robust controllers for the multiple-model set. The switching
control system automatically selects the most appropriate candidate controller into the loop,
according to the errors between current vehicle dynamics and multiple models. This technique
offers more consistent and approximately linear node dynamics for upper level platoon control,
even under relatively large vehicle uncertainties. Simulation comparison with a sliding model
controller and a fixed H-infinity controller is conducted for a passenger car to demonstrate the
enhanced robustness of the switching control method. The experimental test for the same car is
performed for further validation.

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