A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

Maximum-Likelihood Semiblind Equalization of Doubly Selective Channels Using the EM Algorithm

Maximum-likelihood semi-blind joint channel estimation and equalization for doubly selective channels and single-carrier systems is proposed. We model the doubly selective channel as an FIR filter where each filter tap is modeled as a linear combination of basis functions. This channel description is then integrated in an iterative scheme based on the expectation-maximization (EM) principle that converges to the channel description vector estimation. We discuss the selection of the basis functions and compare various functions sets. To alleviate the problem of convergence to a local maximum, we propose an initialization scheme to the EM iterations based on a small number of pilot symbols. We further derive a pilot positioning scheme targeted to reduce the probability of convergence to a local maximum. Our pilot positioning analysis reveals that for high Doppler rates it is better to spread the pilots evenly throughout the data block (and not to group them) even for frequency-selective channels. The resulting equalization algorithm is shown to be superior over previously proposed equalization schemes and to perform in many cases close to the maximum-likelihood equalizer with perfect channel knowledge. Our proposed method is also suitable for coded systems and as a building block for Turbo equalization algorithms

Efficient sequence detection for multicarrier transmissions over doubly dispersive channels

Multicarrier modulation (MCM) over a doubly dispersive (DD) channel yields complicated inter-carrier interference (ICI) and intersymbol interference (ISI) responses. With appropriately designed MCM pulse shapes, however, ISI can be mostly suppressed, as can ICI outside a small subcarrier radius. In this case, the channel can be well described by a quasi-banded subcarrier coupling matrix. Several sequence detectors (SDs) have been proposed to leverage this quasi-banded structure, including linear, decision feedback (DF), and maximum likelihood (ML) schemes. Relative to linear and DF schemes, the ML schemes offer superior performance, but are significantly more complex, even when efficient Viterbi or sphere-detection algorithms are used. In this paper, we propose a new SD algorithm for the quasi-banded application with a frame error rate (FER) that is nearly indistinguishable from ML and an average complexity that is on par with DF SD. 1 1