Dynamic spectrum management (DSM) is an effective technique for mitigating detrimental effect of crosstalk in digital subscriber lines (DSL). Among various DSM techniques, centralized optimal spectrum balancing (OSB) achieves the maximum possible data rates by computing the optimal power spectral densities (PSDs) for all modems in DSL systems.… (More)
(This is the reason for the term harmonized.) Furthermore, its predominantly distributed structure can be implemented in DSL/DSM scenarios with only Level 1 coordination. Simulation results of various cases verify the convergence to the unique optimal solution within 5–10 iterations.
While most existing loading algorithms for xDSL-DMT systems strive for the optimal energy distribution to maximize their rate, the amounts of bits loaded to subcarriers are constrained to be integers and the associated granularity losses can represent a significant percentage of the achievable data rate, especially in the presence of the peak-power… (More)
This paper proposes a centralized optimum spectrum management (OSM) technique with group power constraint (GPC), which jointly determines total transmission power and power spectral densities (PSD) of the different lines to control the crosstalks in a fully collaborative manner for digital subscriber lines (DSL) systems. Dual decomposition is employed to… (More)
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In this paper, we present a system towards Indian postal automation based on PIN (Postal Index Number) code. Since India is a multilingual and multi-script country that was earlier colonized by UK, the address part may be written by combination of scripts such as Latin (English) and a local (state) script. Here, we shall consider Oriya script one of the… (More)
–Multiuser margin maximization algorithms are developed for multi-carrier Digital Subscriber Loops (DSL) employing Dynamic Spectrum Management (DSM). Margin maximization is desirable for constant bit rate applications and provides protection against various non-stationary and bursty noise sources. Most single-user margin maximization algorithms rely on a… (More)
This paper proposes a low-complexity selective iterative water-filling (SIW) algorithm that can considerably enhance the performance of IW. Unlike the highly complicated and centralized OSM, the SIW has a complexity of at most N times that of IW algorithm and is quasi-autonomous requiring very little centralized coordination. Simulation results in realistic… (More)