Pushpika Wijesinghe

Efficient simulation of OFDM and OSTBC-OFDM systems over multipath Rayleigh fading channels

We present an importance sampling (IS) based approach for efficient simulation of Orthogonal Frequency Division Multiplexing Systems (OFDM) operating over multipath fading channels. We derive the optimal biasing parameters for Rayleigh fading multipath channels considering an OFDM system and an OFDM system with Orthogonal Space-Time Block Coded (OSTBC) transmission. The numerical results prove significant computational efficiency gains in the order of 108 in estimating probabilities of the order 10−11.

Efficient simulation of orthogonal frequency division multiplexing systems using importance sampling

This study presents the importance sampling (IS) analysis for the efficient simulation of orthogonal frequency division multiplexing (OFDM) systems. Importance sampling is an efficient rare-event simulation technique that aims at reducing the simulation runtime by reducing the variance of the estimator. The efficiency of IS highly relies on the proper selection of the biased simulation density function. This paper considers the problem of biasing the simulation density function of OFDM systems for achieving higher variance reduction gains and computational efficiencies. In particular, the authors show how to bias the time domain noise density function and how to correct the biased error count at the receiver in the frequency domain of an OFDM system operating over multipath fading channels with minimum mean square error equalisation. Further, the authors obtain the optimum biasing parameters for variance scaling method and mean translation method applied to bias the noise density function. The presented results can easily be generalised to OFDM systems operating over additive white Gaussian noise (AWGN) channels. The simulation results demonstrate that extensive gains in estimator variance reduction can be achieved through the proposed analysis rather than by using conventional Monte-Carlo simulations.

Multicanonical Estimation of Outage Probabilities in MIMO Channels

Communication over Multiple-Input Multiple-Output (MIMO) fading channels is of much interest in the current telecommunication context. Estimation of very small outage probabilities in such channels is an important, yet time consuming task, owing to the lengthy run-time requirements of traditional Monte Carlo (MC) simulations. Hence, fast and accurate methods for estimating outage capacities are of necessity. Importance sampling (IS) has been the most widely used efficient simulation tool for telecommunication networks in the past. However, IS requires an in-depth knowledge of the system to explore the optimal biasing distribution. The method described in this paper uses the concept of Multicanonical Monte Carlo (MMC) for the quick simulation of outage probabilities in MIMO channels. MMC can be considered an adaptive IS technique which employs a blind adaptation algorithm to converge to the optimal biasing distribution. Here, we elaborate the use of MMC and present an algorithm for efficient simulation of outage probabilities of Rayleigh fading MIMO channels. This method can easily be extended to other fading models of interest. Numerical results, which extend the known results in literature, of the MMC simulations in comparison with that of the MC simulations are presented.

An Efficient Algorithm for Capacity and Outage Probability Estimation in MIMO Channels

An efficient algorithm based on a biased Monte Carlo method known as Transition Matrix Monte Carlo (TMMC) is proposed for capacity and outage probability estimation in multiple-input multiple-output (MIMO) communication systems. The algorithm is generally applicable to any fading scenario. A MIMO maximal ratio combining system operating over Nakagami-m fading is used to validate the algorithm.

Fast simulation of OFDM systems over frequency selective fading channels

This paper illustrates the use of the Importance Sampling (IS) technique for efficient simulation of Orthogonal Frequency Division Multiplexing Systems operating over frequency selective fading channels with equalization. In order to achieve higher estimator variance reduction gains, the proper biasing procedure for time domain noise density function and the way of un-biasing the error count at the receiver in frequency domain are shown. Further, the optimum biasing parameters for conventional importance sampling (CIS) and improved importance sampling (IIS) methods are obtained. It is demonstrated, through simulations, that the proposed methods can provide extensive gains in estimator variance reduction and runtime saving compared to the conventional Monte-Carlo (MC) simulations.

Low complexity MAP decoding of tailbiting convolutional codes

Tailbiting is an effective technique to terminate convolutional codes without a rate loss. The latest application of tailbiting codes can be seen in the broadcast channel of the long term evolution (LTE) cellular systems. Due to the high computational complexity of maximum likelihood (ML) decoding of tailbiting codes, suboptimum decoding techniques are often used in practice. In this paper, we propose a low-complexity MAP decoder based on the observation that the MAP decoder can forget the erroneous initial conditions faster in forward calculations than in backward calculations. The proposed decoder uses a head length for forward calculations and a tail length for backward calculations in the well-known BCJR algorithm. This allows the decoder to eliminate the starting and ending transients in the bit error rate that occur due to the uniform initial conditions thereby improving the performance. Using the tailbiting convolutional code proposed for LTE over different channel conditions, it is shown that circular MAP decoding performs close to ML decoding.

Improved multicanonical algorithm for outage probability estimation in MIMO channels

Multicanonical Monte Carlo (MMC) is an adaptive importance sampling technique which employs a blind adaptation algorithm to converge to the optimal biasing distribution. In this paper, we propose an improved MMC algorithm for fast estimation of outage probabilities in Multiple Input Multiple Output (MIMO) channels. The algorithm uses an improved estimator which can provide smooth estimates with high reliability at very low error probabilities. The proposed estimator uses moving average filtering to smooth the visits histograms at each iteration thereby reducing the stochastic fluctuations between iterations. We compare the proposed estimator with the well known Bergs update and the simulation results show that the new estimator can accurately estimate lower error probabilities with the same number of samples.

Tighter performance upper bounds for terminated convolutional codes in Rayleigh fading channels

In this paper, we present tighter performance upper bounds for terminated convolutional codes over Rayleigh fading channels with BPSK and QPSK modulation. The performance upper bounds for convolutional codes are generally obtained from the union bound derived from the transfer function. This bound is quite loose for a terminated trellis. In the literature, performance bounds for terminated convolutional codes with BPSK in AWGN environment have been derived using a new weight enumerator obtained from a modified trellis diagram. In this work, we use the modified trellis approach to derive the weight enumerators for rate 1/2 terminated convolutional codes with QPSK modulation and derive tighter upper bounds using that.

Social Impact of SMS in Sri Lanka

Though Sri Lanka has a relatively low penetration of fixed (landline) phones, mobile phones have made a significant penetration during last six years. The number of mobile subscribers within the island by the end of 2007 was almost 70 times of the customers reported a decade back. A large number of supplementary services have been introduced with the booming increase in the mobile customer base. Short Message Service (SMS) is one such service that has made a significant penetration in Sri Lankan society. Nowadays, SMS has become the major non verbal communication channel among the general public. The cost effectiveness of the service has lead to its popularity within the country. From simple person to person communication to achieving a confidential bank transaction, a vast range of applications have emerged based on SMS. In this paper, we present how Sri Lanka has adopted to SMS. In particular, we investigate the factors causing the popularity of this service in Sri Lanka and its social impact on the island nation.

Combined Flat Histogram Monte Carlo Method for Efficient Simulation of Communication Systems

A modified Monte Carlo (MC) method for efficient sampling of system outputs is derived by combining transition matrix Monte Carlo (TMMC) and Wang-Landau (WL) flat histogram methods. The proposed combination updates the estimation of the WL method using an intermediate estimate derived from the TMMC dynamics such that the variance of the resultant estimate is minimized. Combining the benefits of both methods, the new algorithm can estimate very low probabilities that are not normally reachable by the conventional MC using a realizable sample size.