On the Derivation of Optimal Partial Successive Interference Cancellation

The necessity of accurate channel estimation for Successive and Parallel Interference Cancellation is well known. Iterative channel estimation and channel decoding (for instance by means of the Expectation-Maximization algorithm) is particularly important for these multiuser detection schemes in the presence of time varying channels, where a high density of pilots is necessary to track the channel. This paper designs a method to analytically derive a weighting factor $\alpha$, necessary to improve the efficiency of interference cancellation in the presence of poor channel estimates. Moreover, this weighting factor effectively mitigates the presence of incorrect decisions at the output of the channel decoder. The analysis provides insight into the properties of such interference cancellation scheme and the proposed approach significantly increases the effectiveness of Successive Interference Cancellation under the presence of channel estimation errors, which leads to gains of up to 3 dB.Comment: IEEE GLOBECOM 201

Multiresolution MBMS transmissions for MIMO UTRA LTE systems

Hierarchical constellations constitute a simple technique for achieving multiresolution and, therefore, are appealing for MBMS (Multimedia Broadcast and Multicast Service). In this paper we consider the use of M-QAM hierarchical constellations (Quadrature Amplitude Modulation) combined with MIMO (Multiple Input Multiple Output) for the transmission of multicast and broadcast services in UTRA (Universal Mobile Telecommunications System Terrestrial Radio Access) Long Term Evolution (LTE) systems based on Orthogonal Frequency Division Multiplexing (OFDM). Due to the demanding channel estimation requirements and the high sensitivity to interference resulting from the usage of several antennas and hierarchical constellations, an enhanced receiver based on the turbo concept is employed and its performance is evaluated.info:eu-repo/semantics/acceptedVersio

A Robust Threshold for Iterative Channel Estimation in OFDM Systems

A novel threshold computation method for pilot symbol assisted iterative channel estimation in OFDM systems is considered. As the bits are transmitted in packets, the proposed technique is based on calculating a particular threshold for each data packet in order to select the reliable decoder output symbols to improve the channel estimation performance. Iteratively, additional pilot symbols are established according to the threshold and the channel is re-estimated with the new pilots inserted to the known channel estimation pilot set. The proposed threshold calculation method for selecting additional pilots performs better than non-iterative channel estimation, no threshold and fixed threshold techniques in poor HF channel simulations

Encoded Pilots for Iterative Receiver Improvement

Abstract 1 -This paper proposes a novel iterative channel estimation and low density parity check (LDPC) (not turbo) decoding scheme where the pilot symbols are encoded and can be used for both channel estimation and decoding. To achieve this objective, this paper will employ systematic LDPC codes so that pilot symbols can be encoded as data. In this way, initial channel estimation can be made before decoding by using systematic coded pilot symbols. In addition, the known pilot symbol positions have higher reliability than data and can significantly improve the initial decoding. Moreover, the encoded pilot symbols are not necessary to be transmitted for decoding purpose. So, the encoded pilot symbols can be called artificial symbols. This paper has wide applications in wireless communications systems because many of them require channel estimation and coding

Turbo Detection in Rayleigh flat fading channel with unknown statistics

ABSTRACT The turbo detection of turbo coded symbols over correlated Rayleigh flat fading channels generated according to Jakes' model is considered in this paper. We propose a method to estimate the channel signal-to-noise ratio (SNR) and the maximum Doppler frequency. These statistics are required by the linear minimum mean squared error (LMMSE) channel estimator. To improve the system convergence, we redefine the channel reliability factor by taking into account the channel estimation error statistics. Simulation results for rate 1/3 turbo code and two different normalized fading rates show that the use of the new reliability factor greatly improves the performance. The improvement is more substantial when channel statistics are unknown. K EYWORDS MAP-BCJR decoder, SNR, maximum Doppler frequency, turbo processing, channel reliability

Low Complexity Scalable Iterative Algorithms for IEEE 802.11p Receivers

In this paper, we investigate receivers for Vehicular to Vehicular (V2V) and Vehicular to Infrastructure (V2I) communications. Vehicular channels are characterized by multiple paths and time variations, which introduces challenges in the design of receivers. We propose an algorithm for IEEE 802.11p compliant receivers, based on Orthogonal Frequency Division Multiplexing (OFDM). We employ iterative structures in the receiver as a way to estimate the channel despite variations within a frame. The channel estimator is based on factor graphs, which allow the design of soft iterative receivers while keeping an acceptable computational complexity. Throughout this work, we focus on designing a receiver offering a good complexity performance trade-off. Moreover, we propose a scalable algorithm in order to be able to tune the trade-off depending on the channel conditions. Our algorithm allows reliable communications while offering a considerable decrease in computational complexity. In particular, numerical results show the trade-off between complexity and performance measured in computational time and BER as well as FER achieved by various interpolation lengths used by the estimator which both outperform by decades the standard least square solution. Furthermore our adaptive algorithm shows a considerable improvement in terms of computational time and complexity against state of the art and classical receptors whilst showing acceptable BER and FER performance

Generalized Nearest Neighbor Decoding

It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minimum Euclidean distance between a codeword and the received channel output vector, is the maximum likelihood solution and hence capacity-achieving. Nearest neighbor decoding remains a convenient and yet mismatched solution for general channels, and the key message of this paper is that the performance of the nearest neighbor decoding can be improved by generalizing its decoding metric to incorporate channel state dependent output processing and codeword scaling. Using generalized mutual information, which is a lower bound to the mismatched capacity under independent and identically distributed codebook ensemble, as the performance measure, this paper establishes the optimal generalized nearest neighbor decoding rule, under Gaussian channel input. Several {restricted forms of the} generalized nearest neighbor decoding rule are also derived and compared with existing solutions. The results are illustrated through several case studies for fading channels with imperfect receiver channel state information and for channels with quantization effects.Comment: 30 pages, 8 figure