2,137 research outputs found
Raptor Codes in the Low SNR Regime
In this paper, we revisit the design of Raptor codes for binary input
additive white Gaussian noise (BIAWGN) channels, where we are interested in
very low signal to noise ratios (SNRs). A linear programming degree
distribution optimization problem is defined for Raptor codes in the low SNR
regime through several approximations. We also provide an exact expression for
the polynomial representation of the degree distribution with infinite maximum
degree in the low SNR regime, which enables us to calculate the exact value of
the fractions of output nodes of small degrees. A more practical degree
distribution design is also proposed for Raptor codes in the low SNR regime,
where we include the rate efficiency and the decoding complexity in the
optimization problem, and an upper bound on the maximum rate efficiency is
derived for given design parameters. Simulation results show that the Raptor
code with the designed degree distributions can approach rate efficiencies
larger than 0.95 in the low SNR regime.Comment: Submitted to the IEEE Transactions on Communications. arXiv admin
note: text overlap with arXiv:1510.0772
Massive Non-Orthogonal Multiple Access for Cellular IoT: Potentials and Limitations
The Internet of Things (IoT) promises ubiquitous connectivity of everything
everywhere, which represents the biggest technology trend in the years to come.
It is expected that by 2020 over 25 billion devices will be connected to
cellular networks; far beyond the number of devices in current wireless
networks. Machine-to-Machine (M2M) communications aims at providing the
communication infrastructure for enabling IoT by facilitating the billions of
multi-role devices to communicate with each other and with the underlying data
transport infrastructure without, or with little, human intervention. Providing
this infrastructure will require a dramatic shift from the current protocols
mostly designed for human-to-human (H2H) applications. This article reviews
recent 3GPP solutions for enabling massive cellular IoT and investigates the
random access strategies for M2M communications, which shows that cellular
networks must evolve to handle the new ways in which devices will connect and
communicate with the system. A massive non-orthogonal multiple access (NOMA)
technique is then presented as a promising solution to support a massive number
of IoT devices in cellular networks, where we also identify its practical
challenges and future research directions.Comment: To appear in IEEE Communications Magazin
Design of First-Order Optimization Algorithms via Sum-of-Squares Programming
In this paper, we propose a framework based on sum-of-squares programming to
design iterative first-order optimization algorithms for smooth and strongly
convex problems. Our starting point is to develop a polynomial matrix
inequality as a sufficient condition for exponential convergence of the
algorithm. The entries of this matrix are polynomial functions of the unknown
parameters (exponential decay rate, stepsize, momentum coefficient, etc.). We
then formulate a polynomial optimization, in which the objective is to optimize
the exponential decay rate over the parameters of the algorithm. Finally, we
use sum-of-squares programming as a tractable relaxation of the proposed
polynomial optimization problem. We illustrate the utility of the proposed
framework by designing a first-order algorithm that shares the same structure
as Nesterov's accelerated gradient method
- …