14,355 research outputs found
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Channel Dynamics and SNR Tracking in Millimeter Wave Cellular Systems
The millimeter wave (mmWave) frequencies are likely to play a significant
role in fifth-generation (5G) cellular systems. A key challenge in developing
systems in these bands is the potential for rapid channel dynamics: since
mmWave signals are blocked by many materials, small changes in the position or
orientation of the handset relative to objects in the environment can cause
large swings in the channel quality. This paper addresses the issue of tracking
the signal to noise ratio (SNR), which is an essential procedure for rate
prediction, handover and radio link failure detection. A simple method for
estimating the SNR from periodic synchronization signals is considered. The
method is then evaluated using real experiments in common blockage scenarios
combined with outdoor statistical models
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
In this paper, we present a robust multipath-based localization and mapping
framework that exploits the phases of specular multipath components (MPCs)
using a massive multiple-input multiple-output (MIMO) array at the base
station. Utilizing the phase information related to the propagation distances
of the MPCs enables the possibility of localization with extraordinary accuracy
even with limited bandwidth. The specular MPC parameters along with the
parameters of the noise and the dense multipath component (DMC) are tracked
using an extended Kalman filter (EKF), which enables to preserve the
distance-related phase changes of the MPC complex amplitudes. The DMC comprises
all non-resolvable MPCs, which occur due to finite measurement aperture. The
estimation of the DMC parameters enhances the estimation quality of the
specular MPCs and therefore also the quality of localization and mapping. The
estimated MPC propagation distances are subsequently used as input to a
distance-based localization and mapping algorithm. This algorithm does not need
prior knowledge about the surrounding environment and base station position.
The performance is demonstrated with real radio-channel measurements using an
antenna array with 128 ports at the base station side and a standard cellular
signal bandwidth of 40 MHz. The results show that high accuracy localization is
possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to
the IEEE Transaction on Wireless Communications for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
Privacy-preserving Cross-domain Routing Optimization -- A Cryptographic Approach
Today's large-scale enterprise networks, data center networks, and wide area
networks can be decomposed into multiple administrative or geographical
domains. Domains may be owned by different administrative units or
organizations. Hence protecting domain information is an important concern.
Existing general-purpose Secure Multi-Party Computation (SMPC) methods that
preserves privacy for domains are extremely slow for cross-domain routing
problems. In this paper we present PYCRO, a cryptographic protocol specifically
designed for privacy-preserving cross-domain routing optimization in Software
Defined Networking (SDN) environments. PYCRO provides two fundamental routing
functions, policy-compliant shortest path computing and bandwidth allocation,
while ensuring strong protection for the private information of domains. We
rigorously prove the privacy guarantee of our protocol. We have implemented a
prototype system that runs PYCRO on servers in a campus network. Experimental
results using real ISP network topologies show that PYCRO is very efficient in
computation and communication costs
Indoor wireless communications and applications
Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter
Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing
Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments
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