Robust frequency synchronization for an OFDMA uplink system disturbed by a Cognitive Radio system interference

Abstract

In Cognitive Radio (CR) systems, spectrum sensing plays a key role to determine the free frequency bands. However, when the primaryuser (PU) signal spectrum exhibits localized fading, PU detection cannot be guaranteed. In addition, as the CR may use the PU faded frequencies, the PU spectrum can be disturbed by a narrow-band interference (NBI) and synchronization algorithms used for the PU carrier frequency offset (CFO) estimation suffer degradations. In this paper, we propose a new scheme that jointly allows the CR-NBI to be detected and the PU-CFOs and the channels to be estimated in an orthogonal frequency division multiple access (OFDMA) system. It combines a sigma point Kalman filter and a test aiming at detecting a variation of the measurement-noise covariance matrix. Simulation results confirm that the proposed algorithm can accurately detect the CR-NBI and estimate the PU-CFOs.

Sistemas de Radio Inteligencia de Tipo Overlay: Análisis de Técnicas de Mitigación de Interferencia

“…Para aplicar las técnicas de mitigación de interferencias en los receptores de los usuarios primarios se deben realizar modificaciones físicas en los sistemas actuales [5]. Por consiguiente, es necesario que los usuarios primarios estén dispuestos a realizar estos cambios y que los usuarios secundarios asuman los costos asociados, para considerarse como una opción atractiva.…”

Frequency synchronization and channel equalization for an OFDM-IDMA uplink system

“…However, due to the iterative scheme, these methods may increase the computational complexity of the receiver. In this subsection, we suggest a CFO/channel estimation by means of a SPKF [6]. A preamble of one OFDM-IDMA symbol is used to perform the estimation.…”

“…The advantages of the SPKF is that it does not require calculations of Jacobians or Hessians. The SPKF provide "accurate" estimations as long as the received signal is disturbed by a white Gaussian noise [6]. For details about the SPKF algorithm description, the reader is referred to [9].…”

“…In [5], the authors propose an iterative suboptimal method based on an approximation of a maximum likelihod (ML) estimator. In addition, in [6], we present a robust frequency synchronization using a sigma point Kalman filter (SPKF) based CFO estimation. These methods only deal with OFDMA systems, where the CFO correction can be performed before or after the fast Fourier transform (FFT) step of the OFDM demodulation.…”

“…Let us now define the 1 × U row vector that contains the normalized CFOs and the 1 × ULU row vector that contains the CSIs of each user: The nth sample of the received symbol R(n) depends on (6) and (7). So, let us express the nth sample of the received OFDM-IDMA symbol as:…”