1,101 research outputs found
Efficient Direct Detection of M-PAM Sequences with Implicit CSI Acquisition for The FSO System
Compared to on-off keying (OOK), M-ary pulse amplitude modulation (M-PAM,
M>2) is more spectrally efficient. However, to detect M-PAM signals reliably,
the requirement of accurate channel state information is more stringent.
Previously, for OOK systems, we have developed a receiver that requires few
pilot symbols and can jointly detect the data sequence and estimate the unknown
channel gain implicitly. In this paper, using the same approach, we extend our
previous work and derive a generalized receiver for M-PAM systems. A
Viterbi-type trellis-search algorithm coupled with a selective-store strategy
is adopted, resulting in a low implementation complexity and a low memory
requirement. Therefore, the receiver is efficient in terms of energy, spectra,
implementation complexity and memory. Using theoretical analysis, we show that
its error performance approaches that of maximum likelihood detection with
perfect knowledge of the channel gain, as the observation window length
increases. Also, simulation results are presented to justify the theoretical
analysis.Comment: 6 page
A Robust and Efficient Detection Algorithm for The Photon-Counting Free-Space Optical System
We propose a Viterbi-type trellis-search algorithm to implement the FSO
photon-counting sequence receiver proposed in [1] more efficiently and a
selective-store strategy to overcome the error floor problem observed therein.Comment: 3 page
Listen-and-Talk: Full-duplex Cognitive Radio Networks
In traditional cognitive radio networks, secondary users (SUs) typically
access the spectrum of primary users (PUs) by a two-stage "listen-before-talk"
(LBT) protocol, i.e., SUs sense the spectrum holes in the first stage before
transmit in the second stage. In this paper, we propose a novel
"listen-and-talk" (LAT) protocol with the help of the full-duplex (FD)
technique that allows SUs to simultaneously sense and access the vacant
spectrum. Analysis of sensing performance and SU's throughput are given for the
proposed LAT protocol. And we find that due to self-interference caused by FD,
increasing transmitting power of SUs does not always benefit to SU's
throughput, which implies the existence of a power-throughput tradeoff.
Besides, though the LAT protocol suffers from self-interference, it allows
longer transmission time, while the performance of the traditional LBT protocol
is limited by channel spatial correction and relatively shorter transmission
period. To this end, we also present an adaptive scheme to improve SUs'
throughput by switching between the LAT and LBT protocols. Numerical results
are provided to verify the proposed methods and the theoretical results.Comment: in proceeding of IEEE Globecom 201
Distributed Cooperative Sensing in Cognitive Radio Networks: An Overlapping Coalition Formation Approach
Cooperative spectrum sensing has been shown to yield a significant
performance improvement in cognitive radio networks. In this paper, we consider
distributed cooperative sensing (DCS) in which secondary users (SUs) exchange
data with one another instead of reporting to a common fusion center. In most
existing DCS algorithms, the SUs are grouped into disjoint cooperative groups
or coalitions, and within each coalition the local sensing data is exchanged.
However, these schemes do not account for the possibility that an SU can be
involved in multiple cooperative coalitions thus forming overlapping
coalitions. Here, we address this problem using novel techniques from a class
of cooperative games, known as overlapping coalition formation games, and based
on the game model, we propose a distributed DCS algorithm in which the SUs
self-organize into a desirable network structure with overlapping coalitions.
Simulation results show that the proposed overlapping algorithm yields
significant performance improvements, decreasing the total error probability up
to 25% in the Q_m+Q_f criterion, the missed detection probability up to 20% in
the Q_m/Q_f criterion, the overhead up to 80%, and the total report number up
to 10%, compared with the state-of-the-art non-overlapping algorithm
Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games
Recently, cellular networks are severely overloaded by social-based services,
such as YouTube, Facebook and Twitter, in which thousands of clients subscribe
a common content provider (e.g., a popular singer) and download his/her content
updates all the time. Offloading such traffic through complementary networks,
such as a delay tolerant network formed by device-to-device (D2D)
communications between mobile subscribers, is a promising solution to reduce
the cellular burdens. In the existing solutions, mobile users are assumed to be
volunteers who selfishlessly deliver the content to every other user in
proximity while moving. However, practical users are selfish and they will
evaluate their individual payoffs in the D2D sharing process, which may highly
influence the network performance compared to the case of selfishless users. In
this paper, we take user selfishness into consideration and propose a network
formation game to capture the dynamic characteristics of selfish behaviors. In
the proposed game, we provide the utility function of each user and specify the
conditions under which the subscribers are guaranteed to converge to a stable
network. Then, we propose a practical network formation algorithm in which the
users can decide their D2D sharing strategies based on their historical
records. Simulation results show that user selfishness can highly degrade the
efficiency of data offloading, compared with ideal volunteer users. Also, the
decrease caused by user selfishness can be highly affected by the cost ratio
between the cellular transmission and D2D transmission, the access delays, and
mobility patterns
Listen-and-Talk: Protocol Design and Analysis for Full-duplex Cognitive Radio Networks
In traditional cognitive radio networks, secondary users (SUs) typically
access the spectrum of primary users (PUs) by a two-stage "listen-before-talk"
(LBT) protocol, i.e., SUs sense the spectrum holes in the first stage before
transmitting in the second. However, there exist two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. In this paper, we propose a "listen-and-talk" (LAT)
protocol with the help of full-duplex (FD) technique that allows SUs to
simultaneously sense and access the vacant spectrum. Spectrum utilization
performance is carefully analyzed, with the closed-form spectrum waste ratio
and collision ratio with the PU provided. Also, regarding the secondary
throughput, we report the existence of a tradeoff between the secondary
transmit power and throughput. Based on the power-throughput tradeoff, we
derive the analytical local optimal transmit power for SUs to achieve both high
throughput and satisfying sensing accuracy. Numerical results are given to
verify the proposed protocol and the theoretical results
RECEIVER DESIGN AND PERFORMANCE ANALYSIS FOR FREE-SPACE OPTICAL COMMUNICATIONS
Ph.DDOCTOR OF PHILOSOPH
Real-Time Scheduling for Time-Sensitive Networking: A Systematic Review and Experimental Study
Time-Sensitive Networking (TSN) has been recognized as one of the key
enabling technologies for Industry 4.0 and has been deployed in many time- and
mission-critical industrial applications, e.g., automotive and aerospace
systems. Given the stringent real-time communication requirements raised by
these applications, the Time-Aware Shaper (TAS) draws special attention among
the many traffic shapers developed for TSN, due to its ability to achieve
deterministic latency guarantees. Extensive efforts on the designs of
scheduling methods for TAS shapers have been reported in recent years to
improve the system schedulability, each with their own distinct focuses and
concerns. However, these scheduling methods have yet to be thoroughly
evaluated, especially through experimental comparisons, to provide a
systematical understanding on their performance using different evaluation
metrics in various application scenarios. In this paper, we fill this gap by
presenting a comprehensive experimental study on the existing TAS-based
scheduling methods for TSN. We first categorize the system models employed in
these work along with their formulated problems, and outline the fundamental
considerations in the designs of TAS-based scheduling methods. We then perform
extensive evaluation on 16 representative solutions and compare their
performance under both synthetic scenarios and real-life industrial use cases.
Through these experimental studies, we identify the limitations of individual
scheduling methods and highlight several important findings. This work will
provide foundational knowledge for the future studies on TSN real-time
scheduling problems, and serve as the performance benchmarking for scheduling
method development in TSN.Comment: 22 pages, ac
- …