Receiver design for SPAD-based VLC systems under Poisson-Gaussian mixed noise model

Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadore

Spectral Efficiency and Energy Efficiency of OFDM Systems: Impact of Power Amplifiers and Countermeasures

In wireless communication systems, the nonlinear effect and inefficiency of power amplifier (PA) have posed practical challenges for system designs to achieve high spectral efficiency (SE) and energy efficiency (EE). In this paper, we analyze the impact of PA on the SE-EE tradeoff of orthogonal frequency division multiplex (OFDM) systems. An ideal PA that is always linear and incurs no additional power consumption can be shown to yield a decreasing convex function in the SE-EE tradeoff. In contrast, we show that a practical PA has an SE-EE tradeoff that has a turning point and decreases sharply after its maximum EE point. In other words, the Pareto-optimal tradeoff boundary of the SE-EE curve is very narrow. A wide range of SE-EE tradeoff, however, is desired for future wireless communications that have dynamic demand depending on the traffic loads, channel conditions, and system applications, e.g., high-SE-with-low-EE for rate-limited systems and high-EE-with-low-SE for energy-limited systems. For the SE-EE tradeoff improvement, we propose a PA switching (PAS) technique. In a PAS transmitter, one or more PAs are switched on intermittently to maximize the EE and deliver an overall required SE. As a consequence, a high EE over a wide range SE can be achieved, which is verified by numerical evaluations: with 15% SE reduction for low SE demand, the PAS between a low power PA and a high power PA can improve EE by 323%, while a single high power PA transmitter improves EE by only 68%.Comment: to be published, IEEE J. Sel. Areas Commu

Analytical Characterization and Optimum Detection of Nonlinear Multicarrier Schemes

It is widely recognized that multicarrier systems such as orthogonal frequency division multiplexing (OFDM) are suitable for severely time-dispersive channels. However, it is also recognized that multicarrier signals have high envelope fluctuations which make them especially sensitive to nonlinear distortion effects. In fact, it is almost unavoidable to have nonlinear distortion effects in the transmission chain. For this reason, it is essential to have a theoretical, accurate characterization of nonlinearly distorted signals not only to evaluate the corresponding impact of these distortion effects on the system’s performance, but also to develop mechanisms to combat them. One of the goals of this thesis is to address these challenges and involves a theoretical characterization of nonlinearly distorted multicarrier signals in a simple, accurate way. The other goal of this thesis is to study the optimum detection of nonlinearly distorted, multicarrier signals. Conventionally, nonlinear distortion is seen as a noise term that degrades the system’s performance, leading even to irreducible error floors. Even receivers that try to estimate and cancel it have a poor performance, comparatively to the performance associated to a linear transmission, even with perfect cancellation of nonlinear distortion effects. It is shown that the nonlinear distortion should not be considered as a noise term, but instead as something that contains useful information for detection purposes. The adequate receiver to take advantage of this information is the optimum receiver, since it makes a block-by-block detection, allowing us to exploit the nonlinear distortion which is spread along the signal’s band. Although the optimum receiver for nonlinear multicarrier schemes is too complex, due to its necessity to compare the received signal with all possible transmitted sequences, it is important to study its potential performance gains. In this thesis, it is shown that the optimum receiver outperforms the conventional detection, presenting gains not only relatively to conventional receivers that deal with nonlinear multicarrier signals, but also relatively to conventional receivers that deal with linear, multicarrier signals. We also present sub-optimum receivers which are able to approach the performance gains associated to the optimum detection and that can even outperform the conventional linear, multicarrier schemes

MIMO techniques for higher data rate wireless communications

The demand for higher data rate, higher spectral efficiency and better quality of service in wireless communications is growing fast in the past few years. However, obtaining these requirements become challenging for wireless communication systems due to the problems of channel multi-path fading, higher power loss and power bandwidth limitations. A lot of research interest has been directed towards implementing new techniques in wireless communication systems, such as MIMO an OFDM, to overcome the above mentioned problems. Methods of achieving higher data rate and better spectral efficiency have been dealt with in the thesis. The work comprised three parts; the first part focuses on channel modelling, the second looks at fading mitigation techniques, and the third part deals with adaptive transmission schemes for different diversity techniques. In the first part, we present multiple-input multiple-output (MIMO) space-time geometrical channel model with hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment. The model is based on one-ring scattering assumption. This MIMO model provides statistics of the time of arrival (TOA) and direction of arrival (DOA). Our analytical results are validated with measurement data and compared to different geometrical based signal bounce macro-cell (GBSSBM) channel models including Gaussian scatterer density (GSD) channel model, the geometrical based exponential (GBE) channel model. On the other hand, for the same channel model we investigate the analytical methods which capture physical wave and antenna configuration at both ends representing in a matrix form. In the second part, we investigate the proposed channel model using joint frequency and spatial diversity system. . We combine STBC with OFDM to improve the error performance in the fading channels. We consider two different fading scenarios namely frequency selective and time selective fading channels. For the first scenario we propose a new technique to suppress the frequency error offset caused by the motion of mobile (Doppler shift). On the other hand, we examine the performance of STBC-OFDM in time selective macro-cell channel environment. In the last part, we evaluate the spectral efficiency for different receiver diversity namely maximal ratio combiner (MRC), selection combiner (SC), and Hybrid (MRC/SC). We derive closed form expressions for the single user capacity, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. Three adaptive transmission schemes are analysed: 1) optimal power rate and rate adaptation (opra), constant power with optimal rate adaptation (ora), and 3) channel inversion with fixed rate (cifr). Furthermore, we derive analytical results for capacity statistics including moment generating function (MGF), complementary cumulative distribution function (CDF) and probability density function (pdf)

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems