Joao Guerreiro

Optimum and Sub-Optimum Receivers for OFDM Signals with Strong Nonlinear Distortion Effects

In this paper we consider the optimum detection of OFDM (Orthogonal Frequency Division Multiplexing) signals with strong nonlinear distortion effects. It is shown that the optimum performance with strong nonlinear distortion effects is not as bad as one might expect and can even be better than the performance with conventional, linear transmitters. To achieve these excellent performances we should employ receivers able to take advantage of the information associated to transmitted data symbols that is inherent to the nonlinear distortion component, in opposition to traditional OFDM implementations where nonlinear distortion effects are regarded as an undesirable noise-like component. We study the achievable gains of the optimum receiver both analytically and by simulation. Since the complexity of optimum receivers is extremely high when we have nonlinear distortion effects, even for OFDM signals with a small number of subcarriers, we propose several sub-optimum receivers and evaluate their performance. Our sub-optimal receivers allow remarkable performance improvements, being able to reduce significantly the gap between the optimum performance and the performance of typical OFDM receivers.

Approaching the Maximum Likelihood Performance with Nonlinearly Distorted OFDM Signals

The high envelope fluctuations of OFDM signals (Orthogonal Frequency Division Multiplexing) make them very prone to nonlinear distortion effects. In typical OFDM implementations the nonlinear distortion component is regarded as a noise-like term that leads to performance degradation. To achieve optimum performance we should employ a ML (Maximum Likelihood) receiver where we take into account all the information associated to the transmitted signals that is in the nonlinearly-distorted signal. Although the performance of an ML is substantially better than traditional receivers, its complexity is prohibitively high. In this paper we consider nonlinearly distorted OFDM schemes and we present sub-optimum receivers that try to approach the ML performance. It is shown that, contrarily to what was expectable, the ML performance with nonlinear transmitters can be better than with ideal, linear transmitters. Our suboptimal receivers allow remarkable performance improvements, being able to reduce significantly the gap between the ML performance and the performance of typical OFDM receivers.

Optimum and Sub-Optimum Receivers for OFDM Signals with Iterative Clipping and Filtering

In this paper we consider the optimum ML (Maximum-Likelihood) detection for OFDM signals (Orthogonal Frequency Division Multiplexing) with iterative clipping and filtering. It is shown that the nonlinear distortion does not necessarily mean significant performance degradation and, in fact, the optimum performance could even better than the performance with ideal, linear transmitters. We also present sub-optimum receivers that allow remarkable performance improvements, being able to reduce significantly the gap between the optimum performance and the performance of typical OFDM receivers.

On the Optimum Multicarrier Performance With Memoryless Nonlinearities

It is widely recognized that orthogonal frequency division multiplexing (OFDM) signals are very prone to nonlinear distortion effects, which can lead to significant performance degradation. However, recent results have showed that nonlinear distortion effects do not necessarily mean performance degradation and can actually lead to performance improvements relative to conventional linear OFDM schemes. In this paper, we consider the effects of bandpass memoryless nonlinear devices on OFDM signals and study the optimum asymptotic performance for both nondispersive channels and severely time-dispersive channels. We present analytical methods for obtaining the Euclidean distance between two OFDM signals that are subjected to different nonlinear characteristics. These results are then employed for obtaining the average asymptotic gain relative to conventional linear OFDM schemes in nondispersive channels and the gain distribution for severely time-dispersive channels with Rayleigh-distributed fading on the different multipath components. Our analytical results, which are shown to be very accurate, indicate that the optimum detection of OFDM schemes with strong nonlinear distortion effects allows significant gains when compared with conventional linear OFDM schemes.

On the Detection of CE-OFDM Signals

In this letter, we study the optimum performance of constant envelope orthogonal frequency division multiplexing (CE-OFDM) signals in both ideal additive white Gaussian noise channels and frequency-selective channels, and we compare it to the performance of conventional CE-OFDM receivers based on a phase detector. It is shown that the phase detector can achieve optimum performance, but only in scenarios where the power efficiency is very low. For this reason, the use of CE-OFDM schemes in power-constrained scenarios may demand other type of receivers, such as optimum-based receivers.

Optimum Performance and Spectral Characterization of CE-OFDM Signals

Orthogonal frequency division multiplexing (OFDM) modulations are very popular in wireless communications due to their flexibility and good performance over severely time-dispersive channels. However, OFDM signals have large peak-to-average power ratio (PAPR), which leads to amplification problems. Constant envelope OFDM (CE-OFDM) techniques use an OFDM signal to modulate the phase of a given carrier, allowing a 0 dB PAPR, with all inherent advantages. However, the phase modulator is a nonlinear device that can lead to performance degradation. In this paper, we take advantage of the Gaussian characteristics of OFDM signals to characterize analytically CE-OFDM signals, both in terms of power spectral density (PSD) and optimum asymptotic performance.

ML-based receivers for underwater networks using OFDM signals with strong nonlinear distortion effects

Underwater networks present considerable opportunities as well as technical challenges. Due to severe nature of the underwater acoustic channel, the use of OFDM signals (Orthogonal Frequency Division Multiplexing) with reduced envelope fluctuations is strongly recommendable. Although iterative clipping and filtering techniques are the most efficient way of reducing the envelope fluctuations of OFDM signals, they introduce significant nonlinear distortion effects that lead to performance degradation. In this paper we consider the ML (Maximum-Likelihood) detection of underwater OFDM signals with strong nonlinear distortion effects. It is shown that the nonlinear distortion does not necessarily mean significant performance degradation and, in fact, the ML performance could even be better than the performance with ideal, linear transmitters. We also present sub-optimum ML-based receivers that allow remarkable performance improvements, being able to reduce significantly the gap between the ML performance and the performance of conventional OFDM receivers.

On the Optimum Multicarrier Performance with Memoryless Nonlinearities

One of the major problems associated with multicarrier signals is their high envelope fluctuations that lead to implementation difficulties. Therefore, multicarrier signals are usually submitted to nonlinear operations such as clipping to simplify the power amplification, DAC (Digital-to-Analog Conversion) and other digital signal processing operations. However, these nonlinear operations lead to nonlinear noise that usually is associated with performance degradation. Recently, it was shown that the nonlinear distortion associated to bandpass memoryless nonlinear devices not only does not necessarily means performance degradation, but can even lead to performance gains. In this paper we study the impact of non-bandpass memoryless nonlinearities on the performance of multicarrier signals. We consider both nonlinear devices operating on the real-valued multicarrier signals as well as Cartesian nonlinear devices (also denoted as I-Q nonlinearities) operating separately on the real and imaginary parts of the complex envelope of multicarrier signals. We present a theoretical analysis of the potential performance improvements associated with the optimum detection of multicarrier signals, by deriving accurate theoretical expressions for both the average asymptotic gains in ideal AWGN (Additive White Gaussian Noise) channels and the asymptotic gain distribution for frequency-selective channels with multipath Rayleigh fading.

On the Design of Robust Multi-User Receivers for Base Station Cooperation Systems

BS (Base Station) cooperation schemes allow for an improved overall systems capacity and spectral efficiency. This is due to the possibility of MTs (Mobile Terminals) in adjacent cells sharing the same physical channel. The BSs send a quantized version of the received signals to a central unit that performs the separation of the signals associated to different MTs. In this paper we consider the uplink of BS cooperation schemes with SCFDE (Single-Carrier with Frequency domain Equalization) modulations and receivers based on the IB-DFE (Iterative Block Decision Feedback Equalization) concept for the multi-user detection process. We design robuts receivers that take advantage of the statistical characteristics of the quantization noise.

Energy Consumption Monitoring System for Large Complexes

This paper describes the development of an open source system for monitoring and data acquisition of several energy analyzers. The developed system is based on a computer with Internet/Intranet connection by means of RS485 using Modbus RTU as communication protocol. The monitoring/metering system was developed for large building complexes and was validated in the Faculdade de Ciencias e Tecnologia University campus. The system considers two distinct applications. The first one allows the user to verify, in real time, the energy consumption of any department in the complex, produce load diagrams, tables and print, email or save all available data. The second application keeps records of active/reactive energy consumption in order to verify the existence of some anomalous situation, and also monthly charge energy consumption to each corresponding department.