1,721,424 research outputs found
Integer frequency offset recovery in OFDM transmissions over selective channels
Carrier frequency offset (CFO) in OFDM systems is normally estimated in two steps. The fractional part of the CFO is recovered first and the remaining ambiguity is subsequently resolved by detecting the integer frequency offset (IFO). Conventional IFO recovery algorithms for OFDM signals are sensitive to multipath distortions as they are derived without explicitly taking into account the frequency selectivity of the transmission channel. In this paper, we propose a novel scheme in which the channel response and IFO are jointly estimated using a maximum likelihood (ML) approach. In doing so we exploit one or more pilot blocks placed at the beginning of the frame and carrying known symbols. Since the complexity of the resulting ML algorithm may be relatively large, we also suggest suboptimal solutions unifying various earlier proposals. Computer simulations are used to demonstrate the superiority of the proposed schemes over existing alternatives. It is shown that excellent performance can be achieved with affordable complexity even in the presence of highly dispersive channels
Robust frequency synchronization for OFDM-based cognitive radio systems
Cognitive radio employs spectrum sensing to facilitate coexistence of different communication systems over a same frequency band. A peculiar feature of this technology is the possible presence of interference within the signal bandwidth, which considerably complicates the synchronization task. This paper investigates the problem of carrier frequency estimation in an orthogonal frequency-division multiplexing (OFDM)-based cognitive radio system that operates in the presence of narrowband interference (NBI). Synchronization algorithms devised for conventional OFDM transmissions are expected to suffer from significant performance degradation when the received signal is plagued by NBI. To overcome this difficulty, we propose a novel scheme in which the carrier frequency offset (CFO) and interference power on each subcarrier are jointly estimated through maximum likelihood (ML) methods. In doing so we exploit two pilot blocks. The first one is composed of several repeated parts in the time-domain and provides a CFO estimate which may be affected by a certain residual ambiguity. The second block conveys a known pseudo-noise sequence in the frequency-domain and is used to resolve the ambiguity. The performance of the proposed algorithm is assessed by simulation in a scenario inspired by the IEEE 802.11g WLAN system in the presence of a Bluetooth interferer
A SAGE Approach to Frequency Recovery in OFDM Direct-Conversion Receivers
In-phase/quadrature (I/Q) imbalances are front-end impairments which may greatly complicate the synchronization task in a low-cost direct-conversion receiver (DCR). In this paper we investigate the possibility of using the space-alternating generalized expectation-maximization (SAGE) algorithm to recover the carrier frequency offset in OFDM terminals with a DCR architecture. Our study leads to a novel scheme that operates in a recursive fashion and exploits a conventional OFDM training preamble composed by several repeated parts. At each iteration, interference arising from I/Q impairments is subtracted from the received samples before updating the frequency estimate. The performance of the new scheme is assessed in terms of estimation accuracy and processing load by considering a wireless local area network (WLAN) compliant with the IEEE 802.11a standard. The main goal is to check whether the SAGE approach exhibits some advantages compared to existing alternatives
Transmission modulation system for mobile phone to reduce battery consumption without increasing bit error rate
Carrier frequency offset estimation for OFDM direct-conversion receivers
We investigate the problem of carrier frequency offset (CFO) recovery in an OFDM direct-conversion receiver plagued by both dc-offset and frequency-selective I/Q imbalance. In order to enlarge the frequency acquisition range, the CFO is divided into an integer part, which is multiple of the subcarrier spacing, plus a remaining fractional part. The fractional CFO is firstly estimated by resorting to the least-squares (LS) principle using a suitably designed training sequence. Since the exact LS solution requires a complete search over the frequency uncertainty range, we propose a simpler scheme that dispenses from any peak-search procedure. We also derive an approximated closed-form expression of the estimation accuracy that reveals useful for assessing the impact of various design parameters on the system performance. After computing the fractional CFO, the integer frequency error is eventually retrieved by following a weighted LS approach. Numerical simulations and theoretical analysis indicate that the proposed scheme can be used to obtain accurate CFO estimates with affordable complexity
Fine carrier and sampling frequency synchronization in OFDM systems
This paper investigates the joint pilot-assisted estimation of the residual carrier frequency offset (RCFO) and sampling frequency offset (SFO) in an orthogonal frequency division multiplexing (OFDM) system. As it is known, the exact maximum-likelihood (ML) solution to this problem involves a bidimensional grid-search that cannot be pursued in practice. After introducing an enlarged set of auxiliary unknown parameters, however, the RCFO and SFO recovery tasks can be decoupled and the bidimensional search is thus replaced with a simpler mono-dimensional search. This results into an estimation algorithm of reasonable complexity which is suitable for practical implementation. To further reduce the processing load, we also present an alternative scheme yielding frequency estimates in closed-form. Numerical simulations indicate that the proposed methods outperform existing estimators available in the literature in terms of both estimation accuracy and error-rate performance
A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems
Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through heuristic reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance
A Resource Allocator for the Uplink of Multi-Cell OFDMA Systems
We propose a simple distributed radio resource allocation algorithm for an OFDMA cellular system, which aims at minimizing the overall transmitted power subject to a rate constraint for each user. In order to reduce the problem complexity we use a single modulation; simulations show that the resulting performance degradation is negligible when the number of users is high enough. Moreover, we propose a simple distributed heuristic that, by reducing the rate constraints, steers the multicell system towards an stable resource allocation. Results show that the proposed system exhibits a great robustness to the destructive effects of multiple access interference
Joint Maximum Likelihood Estimation of CFO, Noise Power, and SNR in OFDM Systems
Estimation of noise power and signal-to-noise ratio (SNR) are fundamental tasks in wireless communications. Existing methods to recover these parameters in orthogonal frequency-division multiplexing (OFDM) are derived by following heuristic arguments and assuming perfect carrier frequency offset (CFO) synchronization. Hence, it is currently unknown how they compare with an optimum scheme performing joint maximum likelihood (ML) estimation of CFO, noise power and SNR. In the present work, the joint ML estimator of all these parameters is found by exploiting the repetitive structure of a training preamble composed of several identical parts. It turns out that CFO recovery is the first task that needs to be performed. After CFO compensation, the ML estimation of noise power and SNR reduces to a scheme that is available in the literature, but with a computational saving greater than 60% with respect to the original formulation. To assess the ultimate accuracy achievable by the ML scheme, novel expressions of the Cramer-Rao bound for the joint estimation of all unknown parameters are provided
- …
