Fast Decoder for Overloaded Uniquely Decodable Synchronous Optical CDMA

In this paper, we propose a fast decoder algorithm for uniquely decodable (errorless) code sets for overloaded synchronous optical code-division multiple-access (O-CDMA) systems. The proposed decoder is designed in a such a way that the users can uniquely recover the information bits with a very simple decoder, which uses only a few comparisons. Compared to maximum-likelihood (ML) decoder, which has a high computational complexity for even moderate code lengths, the proposed decoder has much lower computational complexity. Simulation results in terms of bit error rate (BER) demonstrate that the performance of the proposed decoder for a given BER requires only 1-2 dB higher signal-to-noise ratio (SNR) than the ML decoder.Comment: arXiv admin note: substantial text overlap with arXiv:1806.0395

Uniquely Decodable Ternary Codes for Synchronous CDMA Systems

In this paper, we consider the problem of recursively designing uniquely decodable ternary code sets for highly overloaded synchronous code-division multiple-access (CDMA) systems. The proposed code set achieves larger number of users $K < K_{max}^t$ than any other known state-of-the-art ternary codes that offer low-complexity decoders in the noisy transmission. Moreover, we propose a simple decoder that uses only a few comparisons and can allow the user to uniquely recover the information bits. Compared to maximum likelihood (ML) decoder, which has a high computational complexity for even moderate code length, the proposed decoder has much lower computational complexity. We also derived the computational complexity of the proposed recursive decoder analytically. Simulation results show that the performance of the proposed decoder is almost as good as the ML decoder.Comment: arXiv admin note: text overlap with arXiv:1806.0395

Fast Decoder for Overloaded Uniquely Decodable Synchronous CDMA

We consider the problem of designing a fast decoder for antipodal uniquely decodable (errorless) code sets for overloaded synchronous code-division multiple access (CDMA) systems where the number of signals K_{max}^a is the largest known for the given code length L. The proposed decoder is designed in a such a way that the users can uniquely recover the information bits with a very simple decoder, which uses only a few comparisons. Compared to maximum-likelihood (ML) decoder, which has a high computational complexity for even moderate code length, the proposed decoder has a much lower computational complexity. Simulation results in terms of bit error rate (BER) demonstrate that the performance of the proposed decoder only has a 1-2 dB degradation at BER of 10^{-3} when compared to ML

Mobile Health (mHealth) in the Developing World: Two Decades of Progress or Retrogression

Mobile healthcare, or mHealth, is one of the key pillars of information and communication technologies for healthcare that consists of telemedicine, telehealth, eHealth, and mHealth. In the past two decades, mobile health has become a transformative concept for healthcare delivery innovations on a global scale. The success was based on the market-driven strategies that utilised the advances in mobile communications, computing, and sensor technologies, especially in recent years. Those market-driven mobile health systems were also closely associated with the global proliferation of smartphones, and based on the correlated usage principle of the smartphone applications for healthcare and wellbeing. However, the global commercial success of the smartphone-based mHealth model was not widely translated into successful scaled-up and tangible healthcare benefits, especially in low- and-middle income countries, compared to the consumer mobile health markets. The numerous healthcare challenges in the developing world remained largely untackled by the existing mobile health systems and models. The much-hyped transformative benefits of these systems remain largely unfulfilled. For two decades since the inception of this concept, the majority of the population in resource-limited healthcare settings still remain in poorer health and live in worsened conditions, with limited if any access to basic healthcare services. The much-hyped mobile health services that promised transforming these fragile and limited healthcare conditions, did not come to wider fruition globally. The COVID-19 pandemic, with its devastating human and economic impact worsened this status. An overview of the origin and the basic principles of mobile health, its current landscape and status in the developing world is presented. The impact of the smartphone-centric model that dominated the landscape of mobile health systems in these countries is discussed, and a critical view on the limitation of this mobile health model adopted widely in these settings is provided

Multiway Physical-Layer Network Coding via Uniquely Decodable Codes

We focus on a multiway relay channel (MWRC) network where two or more users simultaneously exchange information with each other through the help of a relay node. We propose for the first time to apply ternary uniquely decodable (UD) code sets that we have developed to allow each user to uniquely recover the information bits from the noisy channel environment. One of the key features of the proposed scheme is that it utilizes a very simple decoding algorithm, which requires only a few logical comparisons. Simulation results in terms of bit error rate (BER) demonstrate that the performance of the proposed decoder is almost as good as the maximum-likelihood (ML) decoder. In addition to that through simulations, we show that the proposed scheme can significantly improve the sum-rate capacity, which in turn can potentially improve overall throughput, as it needs only two time slots (TSs) to exchange information compared to the conventional methods

Low-density spreading codes for NOMA systems and a Gaussian separability based design

Improved low-density spreading (LDS) code designs based on the Gaussian separability criterion are conceived. We show that the bit-error-rate (BER) hinges not only on the minimum distance criterion, but also on the average Gaussian separability margin. If two code sets have the same minimum distance, the code set having the highest Gaussian separability margin will lead to a lower BER. Based on the latter criterion, we develop an iterative algorithm that converges to the best known solution having the lowest BER. Our improved LDS code set outperforms the existing LDS designs in terms of its BER performance both for binary phase-shift keying (BPSK) and for quadrature amplitude modulation (QAM) transmissions. Furthermore, we use an appallingly low-complexity minimum mean-square estimation (MMSE) and parallel interference cancellation (PIC) (MMSE-PIC) technique, which is shown to have comparable BER performance to the potentially excessive-complexity maximum-likelihood (ML) detector.This MMSE-PIC algorithm has a much lower computational complexity than the message passingalgorithm (MPA)

NOMA Computation Over Multi-Access Channels for Multimodal Sensing

An improved mean squared error (MSE) minimization solution based on eigenvector decomposition approach is conceived for wideband non-orthogonal multiple-access based computation over multi-access channel (NOMA-CoMAC) framework. This work aims at further developing NOMA-CoMAC for next-generation multimodal sensor networks, where a multimodal sensor monitors several environmental parameters such as temperature, pollution, humidity, or pressure. We demonstrate that our proposed scheme achieves an MSE value approximately 0.7 lower at E_b/N_o = 1 dB in comparison to that for the average sum-channel based method. Moreover, the MSE performance gain of our proposed solution increases even more for larger values of subcarriers and sensor nodes due to the benefit of the diversity gain. This, in return, suggests that our proposed scheme is eminently suitable for multimodal sensor networks