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Solving Sudoku puzzles is formulated as an optimization problem over a set of probabilities. The constraints for a given puzzle translate into a convex polyhedral feasible set for the probabilities. The solution to the puzzle lies at an extremal point of the polyhedron where the probabilities are either zero or one and the entropy is zero. Because the entropy is positive at all other feasible points, an entropy minimization approach is adopted to solve Sudoku. To escape local entropy minima at nonsolution extremal points, a search procedure is proposed in which each iteration involves solving a simple convex optimization problem. This approach is evaluated on thousands of puzzles spanning four levels of difficulty from “easy” to “evil”. [ABSTRACT FROM PUBLISHER]

This paper introduces Bayes risk (expected loss) as a criterion for linear equalization. Since the probability of error is equal to the Bayes risk (BR) for a particular binary loss function, this work is a natural generalization of previous works on minimum probability of error (PE) equalizers. Adaptive equalization algorithms are developed that minimize the BR. Like the minimum PE equalizers, the BR algorithms have low computational complexity which is comparable to that of the LMS algorithm. The advantage of the BR criterion is that the loss function can be specified in a manner that accelerates adaptive equalizer convergence relative to the minimum PE adaptive algorithm as illustrated in simulation examples. Besides introducing a new criterion, this paper provides another independent contribution to the field of PE minimizing equalization. While most prior works focus on M-ary QAM type modulations with rectangular decision regions, this paper uses upper bounds on the probabilities of certain events to yield tractable mathematics that apply to two-dimensional constellations with arbitrarily shaped decision regions. The resulting adaptive algorithm use the full information available in the phase of the error signal, whereas previous algorithms use a quantized version of this error phase. [ABSTRACT FROM AUTHOR]

This paper considers the problem of phase recovery of QPSK signals with phase-locked loops (PLL) using two new phase error detectors (PEDs) which are designed to minimize the probability of making a symbol decision error. The new PEDs resemble the PED derived from the maximum likelihood criterion. However, the new EDs penalize matched filter outputs that are close to decision region boundaries. This penalty gives rise to faster converging PLLs relative to PLLs using the maximum likelihood PED, as shown in simulation results. The S-curves for the PEDs are used as a tool to gain insight into the behavior of the new PEDs. [ABSTRACT FROM AUTHOR]

This paper explores the use of kurtosis in synchronizing with a QPSK burst transmission. The start and end of the burst are a priori unknown and are detected without the use of pilot signals. After frame level synchronization, signal level synchronization is performed. The symbol timing, carrier frequency and carrier phase are recovered without the assistance of known symbols or synchronization words in the data stream, i.e. totally blind synchronization. The performance of frame, symbol and carrier synchronization algorithms is evaluated through computer simulations. [ABSTRACT FROM AUTHOR]

Backscatter radio is an intriguing technology for Internet of Things applications, which enables ultra-low-power devices to communicate with each other. Most of the existing works on the combination of the backscatter communications and the “harvest-then-transfer” (HTT) protocol focus on the throughput maximization, yet the study on the energy efficiency (EE) maximization is still lacking. Driven by this observation, this paper studies the EE maximization for an RF-powered backscatter network with the HTT protocol. Multiple hybrid devices (HDs) can either use the backscatter mode by backscattering energy signals from the power beacon (PB) to the reader or use the HTT protocol to first harvest energy from the PB, and then to transmit data to the reader. The proposed scheme aims to optimize multiple parameters including PB's transmit power and time, HDs’ transmit power and time allocation between the backscatter mode and the HTT mode for maximizing the EE of all the HDs. An iterative algorithm is developed to find the optimal solution for the proposed resource allocation scheme. Simulation results demonstrate the superiority of the proposed scheme in terms of EE of all the HDs. [ABSTRACT FROM AUTHOR]

In this paper, rate and subcarrier bandwidth adaptation (RSBA) on the average spectral efficiency of orthogonal frequency-division multiplexing (OFDM) systems using $M$-ary quadrature amplitude modulation ($M$-QAM) is investigated in the presence of frequency-selective and very rapidly time-varying fading channels. The closed-form expressions for rate and capacity with perfect channel state information (CSI) and imperfect CSI are derived. In this paper, imperfect CSI is caused jointly by channel estimation error and unavoidable delay between when CSI is estimated and when the estimation results are used for actual transmission. The capacity with perfect CSI is just a special case of imperfect CSI. Based on the closed-form expressions of the maximum capacity, optimal RSBA algorithms with perfect and imperfect CSI are proposed, respectively. Theoretical and numerical results show that the RSBA scheme can improve the system performance effectively under the perfect-CSI case. It can make a tradeoff between intercarrier interference (ICI) and transmission efficiency by considering the cyclic prefix. The results also show that the RSBA scheme is effective in repelling the impact of outdated CSI, as well as in reducing the impact of channel estimation error, but to a lesser extent. [ABSTRACT FROM AUTHOR]