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In this paper, we propose a low complexity algorithm for decoding where network coding is deployed in client-server networks. We consider battery powered clients, so that minimizing their power consumptions is essential. Our focus is thus on developing a decoding algorithm that can reduce the computational complexity. Unlike general decoding algorithms that are based on Gaussian elimination, we propose...
In this paper, the belief propagation (BP) based approximation methods which are introduced for low density parity check (LDPC) codes in literature are adapted to the Raptor decoder structure in order to reduce its computational complexity. The bit error rate (BER) performances of the algorithms over the additive white Gaussian noise (AWGN) channel are obtained by both theoretical works and simulations...
One of the main impairments for advanced digital subscriber line (DSL) systems is crosstalk. Crosstalk can be effectively cancelled using vectoring. However, some challenges such as implementation and computational complexities associated with full users' coordination when the number of DSL lines is large or when they are not co-located at any end make full vectoring impractical in many scenarios...
This article presents a simple, less computational complexity method for constructing exponent matrix (3, K) having girth at least 8 of quasi-cyclic low-density parity-check (QC-LDPC) codes based on subtraction method. The construction of code deals with the generation of exponent matrix by three formulas. This method is flexible for any block-column length K. The simulations are shown in comparison...
We address the problem of channel estimation in a large multiple-input multiple-output (MIMO) system using pilot symbol aided algorithm in Rayleigh fading environment. Conventional minimum mean square error and minimum variance unbiased based channel estimators require the inversion of covariance matrices, which has computational complexity of the order of N^6, where N is the number of antennas at...
State of the art Random Linear Network Coding (RLNC) schemes assume that data streams generate packets with equal sizes. This is an assumption that results in the highest efficiency gains for RLNC. A typical solution for managing unequal packet sizes is to zero-pad the smallest packets. However, the efficiency of this strategy depends heavily on the packet size distribution and can significantly curb...
In this letter, belief propagation (BP) based approximation methods for low density parity check (LDPC) codes are adapted to the Luby transform (LT) soft decoder structure in order to reduce its computational complexity. The bit error rate (BER) performances of the algorithms over the binary input additive white Gaussian noise (BIAWGN) channel are obtained by both theoretically and simulations. For...
A hybrid sub-optimal technique has been proposed in this paper for decoding the LDPC codes, which delivers a better performance. The two decoding algorithms namely, the Sum Product Algorithm (SPA) and One Step Majority Logic Decoding Algorithm (OSMLGD) are pooled together to accomplish decoding of LDPC codes. Also the two algorithms are implemented exclusively in order to compare the performance....
In this paper, a simple but efficient permutation enhanced parallel reconstruction architecture for compressive sampling (CS) is proposed. In this architecture, a measurement matrix is constructed from a block-diagonal sensing matrix, the sparsifying basis of the target signal, and a pre-defined permutation matrix. In this way, the projection of the signal onto the sparsifying basis can be divided...
We propose a verification-based algorithm for noiseless Compressed Sensing that reconstructs the original signal operating on a sparse graph. The proposed scheme has affordable computational complexity and its performance is significantly better than previous verification-based algorithms and similar to AMP-based algorithms. We also show that the performance of a noiseless compressed sensing scheme...
Due to its advantage of performance over other algorithms, successive cancellation list (SCL) decoding has become one of the most favorable algorithms for polar codes. However, it still suffers a lot from the linear increasing complexity with list size l. In this paper, an adaptive SCL polar decoder based relaxed sorting (RS) approach is proposed, which successfully reduces the sorting complexity...
Turbo equalization is an iterative approach to perform joint equalization and decoding of data, which is protected by error correction code and transmitted over intersymbol interference (ISI) channels. Turbo equalization for Reed Solomon (RS) code, which is a popular error-correction code in wireless communication and recording systems, is seldom discussed in the literature. In this paper, we investigate...
Spectrum sculpting (SS) is a precoding scheme for sidelobe suppression of orthogonal frequency division multiplexing (OFDM) signals and can shape a spectrum with deep notches at chosen frequencies. However, the SS method will degrade the error rate as the number of notched frequencies increases. Orthogonal precoding of the SS has both a notched spectrum and an ideal error rate, but the computational...
Search algorithms that reduce the time to solve the direct model predictive control (MPC) problem are proposed in this paper. By allowing for suboptimal solutions, the computational complexity of the underlying optimization problem can be significantly reduced, albeit by sacrificing (to a certain degree) optimality. Two approaches are presented and discussed. The first approach requires quadratic...
Power consumption minimization in Wireless Sensor Networks (WSNs) has been discussed extensively in literature. Usually, a central node (a receiver) in WSNs consumes large amount of power due to the necessity to decode every received packet regardless of the fact that the transmission may suffer from packets collision. Current collision detection mechanisms in WSNs have largely been revolving around...
This paper considers the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. We propose efficient algorithms achieving the exact ML non-coherent data detection, for both constant-modulus constellations and nonconstant-modulus constellations. Despite a large number of unknown channel coefficients in massive SIMO...
Wireless Sensor Networks (WSNs) have been considered one of the very promising technologies for the implementation of smart grid. WSN-based smart grid communication protocols have been focused on extending the node's lifetime which is heavily depends on the energy consumption of the node. Since wireless sensors are typically deployed in an ad hoc fashion and operate off of a limited energy source,...
In this paper, we propose a near-optimal multiple-input multiple-output (MIMO) detection algorithm with low and fixed complexity, which is based on the fixed-complexity sphere decoder (FSD). By employing the lattice reduction (LR) to the FSD, the computational complexity is reduced considerably while maintaining the near-optimal bit-error-rate (BER) performance. Although the application of LR to the...
This paper proposes an improved Logarithmic Maximum A Posteriori (Log-MAP) algorithm for Turbo decoding in the Third Generation Partnership Project Long Term Evolution (3GPP LTE). In the proposed algorithm, we exploit the understanding of polynomial regression function to approximately compute the logarithm term (also called correction function) in the Jacobian logarithmic function. The goal is to...
In this paper, we tackle the compressive phase retrieval problem in the presence of noise. The noisy compressive phase retrieval problem is to recover a K-sparse complex signal s ∈ ℂn, from a set of m noisy quadratic measurements: yi = |aiHs|2 + wi; where aiH ∈ ℂn is the ith row of the measurement matrix A ∈ ℂm×n, and wi is the additive noise to the ith measurement. We consider the regime where K...
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