Low-complexity a posteriori probability approximation in EM-based channel estimation for trellis-coded systems

When estimating channel parameters in linearly modulated communication systems, the iterative expectation-maximization (EM) algorithm can be used to exploit the signal energy associated with the unknown data symbols. It turns out that the channel estimation requires at each EM iteration the a posteriori probabilities (APPs) of these data symbols, resulting in a high computational complexity when channel coding is present. In this paper, we present a new approximation of the APPs of trellis-coded symbols, which is less complex and requires less memory than alternatives from literature. By means of computer simulations, we show that the Viterbi decoder that uses the EM channel estimate resulting from this APP approximation experiences a negligible degradation in frame error rate (FER) performance, as compared to using the exact APPs in the channel estimation process

KL-Divergence Guided Two-Beam Viterbi Algorithm on Factorial HMMs

This thesis addresses the problem of the high computation complexity issue that arises when decoding hidden Markov models (HMMs) with a large number of states. A novel approach, the two-beam Viterbi, with an extra forward beam, for decoding HMMs is implemented on a system that uses factorial HMM to simultaneously recognize a pair of isolated digits on one audio channel. The two-beam Viterbi algorithm uses KL-divergence and hierarchical clustering to reduce the overall decoding complexity. This novel approach achieves 60% less computation compared to the baseline algorithm, the Viterbi beam search, while maintaining 82.5% recognition accuracy.Ope

EM based channel estimation in an amplify-and-forward relaying network

Cooperative communication offers a way to obtain spatial diversity in a wireless network without increasing hardware demands. The different cooperation protocols proposed in the literature [1] are often studied under the assumption that all channel state information is available at the destination. In a practical scenario, channel estimates need to be derived from the broadcasted signals. In this paper, we study the Amplify-and-Forward protocol and use the expectation-maximization (EM) algorithm to obtain the channel estimates in an iterative way. Our results show that the performance of the system that knows the channels can be approached at the cost of an increased computational complexity. In case a small constellation is used, a low complexity approximation is proposed with a similar performance

EM based channel estimation in an amplify-and-forward relaying network

Cooperative communication offers a way to obtain spatial diversity in a wireless network without increasing hardware demands. The different cooperation protocols proposed in the literature [1] are often studied under the assumption that all channel state information is available at the destination. In a practical scenario, channel estimates need to be derived from the broadcasted signals. In this paper, we study the Amplify-and-Forward protocol and use the expectation-maximization (EM) algorithm to obtain the channel estimates in an iterative way. Our results show that the performance of the system that knows the channels can be approached at the cost of an increased computational complexity. In case a small constellation is used, a low complexity approximation is proposed with a similar performance

Efficient Direct Detection of M-PAM Sequences with Implicit CSI Acquisition for The FSO System

Compared to on-off keying (OOK), M-ary pulse amplitude modulation (M-PAM, M>2) is more spectrally efficient. However, to detect M-PAM signals reliably, the requirement of accurate channel state information is more stringent. Previously, for OOK systems, we have developed a receiver that requires few pilot symbols and can jointly detect the data sequence and estimate the unknown channel gain implicitly. In this paper, using the same approach, we extend our previous work and derive a generalized receiver for M-PAM systems. A Viterbi-type trellis-search algorithm coupled with a selective-store strategy is adopted, resulting in a low implementation complexity and a low memory requirement. Therefore, the receiver is efficient in terms of energy, spectra, implementation complexity and memory. Using theoretical analysis, we show that its error performance approaches that of maximum likelihood detection with perfect knowledge of the channel gain, as the observation window length increases. Also, simulation results are presented to justify the theoretical analysis.Comment: 6 page

Convolutional coded dual header pulse interval modulation for line of sight photonic wireless links.

The analysis and simulation for convolutional coded dual header pulse interval modulation (CC-DH-PIM) scheme using a rate ½ convolutional code with the constraint length of 3 is presented. Decoding is implemented using the Viterbi algorithm with a hard decision. Mathematical analysis for the slot error rate (SER) upper bounds is presented and results are compared with the simulated data for a number of different modulation techniques. The authors show that the coded DH-PIM outperforms the pulse position modulation (PPM) scheme and offers >4 dB code gain at the SER of 10?4 compared to the standard DH-PIM. Results presented show that the CC-DH-PIM with a higher constraint length of 7 offers a code gain of 2 dB at SER of 10?5 compared to the CC-DH-PIM with a constraint length of 3. However, in CC-DH-PIM the improvement in the error performance is achieved at the cost of reduced transmission throughput compared to the standard DH-PIM

Minimum mean-squared error iterative successive parallel arbitrated decision feedback detectors for DS-CDMA systems

In this paper we propose minimum mean squared error (MMSE) iterative successive parallel arbitrated decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems. We describe the MMSE design criterion for DF multiuser detectors along with successive, parallel and iterative interference cancellation structures. A novel efficient DF structure that employs successive cancellation with parallel arbitrated branches and a near-optimal low complexity user ordering algorithm are presented. The proposed DF receiver structure and the ordering algorithm are then combined with iterative cascaded DF stages for mitigating the deleterious effects of error propagation for convolutionally encoded systems with both Viterbi and turbo decoding as well as for uncoded schemes. We mathematically study the relations between the MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback. Simulation results for an uplink scenario assess the new iterative DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation methods against existing ones