Iancu Avram

Quantize and Forward Cooperative Communication: Channel Parameter Estimation

Cooperative communication systems can effectively be used to combat fading. A cooperative protocol that can be used with half-duplex terminals is the Quantize and Forward (QF) protocol, in which the relay quantizes the information received from the source before forwarding it to the destination. While the outage behavior and error performance of the QF protocol have been investigated extensively, only few research has been performed on the effects of channel parameter estimation. In this contribution, estimates are derived for all communication channels involved, while keeping the complexity of the relay terminal unaltered. First, channel estimates are calculated using known pilot symbols sent by the source and relay. Thereafter, these pilot-based channel estimates are refined using a code-aided Expectation Maximization (EM) approach, yielding an error performance that is very close to that of a system in which the channel parameters are assumed to be known.

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.

The Cramer-Rao Bound for channel estimation in block fading Amplify-and-Forward relaying networks

In this paper, we express the Cramer-Rao Bound (CRB) for channel coefficient and noise variance estimation at the destination of an Amplify-and- Forward (AF) based cooperative system, in terms of the a posteriori expectation of the codewords. An algorithm based on factor graphs can be applied in order to calculate this expectation. As the computation of the CRB is rather intensive, the modified CRB (MCRB), which is a looser bound, is derived in closed form. It can be shown that the MCRB coincides with the CRB in the high signal-to-noise ratio (SNR) limit and to that end the CRB/MCRB ratio is simulated in case of uncoded and convolutional encoded transmission.

A novel quantize-and-forward cooperative system: channel estimation and M-PSK detection performance

A method to improve the reliability of data transmission between two terminals without using multiple antennas is cooperative communication, where spatial diversity is introduced by the presence of a relay terminal. The Quantize and Forward (QF) protocol is suitable to implement in resource constraint relays, because of its low complexity. In prior studies of the QF protocol, all channel parameters are assumed to be perfectly known at the destination, while in reality these need to be estimated. This paper proposes a novel quantization scheme, in which the relay compensates for the rotation caused by the source-relay channel, before quantizing the phase of the received M-PSK data symbols. In doing so, channel estimation at the destination is greatly simplified, without significantly increasing the complexity of the relay terminals. Further, the destination applies the expectation maximization (EM) algorithm to improve the estimates of the source-destination and relay-destination channels. The resulting performance is shown to be close to that of a system with known channel parameters.

Quantize and forward cooperative communication: Joint channel and frequency offset estimation

Cooperative communication systems can effectively be used to combat fading. A cooperative protocol that can be used with half-duplex terminals is the quantize and forward (QF) protocol, in which the relay quantizes the information received from the source before forwarding it to the destination. Most studies on the QF protocol are carried out under the assumption of perfect channel state information (CSI) at the destination, which is not often the case in real-life systems. Therefore, in the present contribution, the effect of incomplete CSI is analyzed for flat Rayleigh fading channels with a frequency offset. To limit the complexity of the estimation, the destination terminal assumes that the relay operates in an amplify and forward (AF) mode. By using the expectation maximization (EM) algorithm to refine the initial pilot-based estimates, the resulting error performance can be made very close to that of a system with perfect CSI.

Maximum-likelihood channel estimation in block fading amplify-and-forward relaying networks

Several diversity techniques have been proposed to counteract the effect of fading on the error performance of wireless networks. A recent and promising technique, which achieves spatial diversity without increased hardware demands, is cooperative communication, involving other terminals in the network that relay the information broadcasted by the source terminal to the destination terminal. In literature several cooperative protocols have been studied under the simplifying assumption that all channel state information is available at the destination. In this paper, we use the space-alternating generalized expectation-maximization (SAGE) algorithm to perform codeaided iterative channel estimation from the broadcasted signals in an Amplify-and-Forward protocol, and investigate the resulting error performance.

Iterative SAGE-Based Channel Estimation in a Block Fading Amplify-and-Forward Relaying Network

Several diversity techniques have been proposed to cope with fading in wireless networks. A recent and promising technique, which does not increase hardware demands, is cooperative communication. Here spatial diversity is created by using other terminals to relay the information from the source terminal to the destination terminal. Cooperative protocols proposed in literature are often studied under the simplifying assumption that all channel state information is available at the destination. This contrasts to a practical scenario where channel estimates need to be derived from the broadcasted signals. In this paper, we focus on the Amplify-and-Forward protocol and use the Space-Alternating Generalized Expectation-maximization (SAGE) algorithm to estimate the channel gain and noise variance in an iterative way, exploiting both the pilot part and the data part of the signal received at the destination. We consider a relay that performs a general affine transformation on the pilot symbols received by the source, and we optimize this transformation in terms of estimation accuracy. The resulting mean square error performance is shown to be close to the Cramer-Rao lower bound (CRB).

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.

Low-complexity quantize-and-forward cooperative communication using two-way relaying

Cooperative communication is used as an effective measure against fading in wireless communication systems. In a classical one-way cooperative system, the relay needs as many orthogonal channels as the number of terminal it assists, yielding a poor spectral efficiency. Efficiency is improved in two-way relaying systems, where a relay simultaneously assists two terminals using only one timeslot. In the current contribution, a two-way quantize-and-forward (QF) protocol is presented. Because of the coarse quantization, the proposed protocol has a low complexity at the relay and can be used with half-duplex devices, making it very suitable for low-complexity applications like sensor networks. Additionally, channel parameter estimation is discussed. By estimating all channel parameters at the destination terminals, relay complexity is kept low. Using Monte Carlo simulations, it is shown that the proposed QF protocol achieves a good frame error rate (FER) performance as compared to two-way amplify-and-forward (AF) and one-way relaying systems. It is further shown that, using the proposed estimation algorithm, the FER degradation arising from the channel parameter estimation is negligible when compared to an (unrealistic) system in which all parameters are assumed to be known.

The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

The quantize-and-forward (QF) cooperative protocol can effectively be used to combat fading in systems using half-duplex relay terminals. While the outage behavior of the QF protocol has been extensively investigated, few research has been performed on the impact of imperfect channel estimates. In this contribution, a lower bound (LB) on the estimation error is obtained for a one-hop relaying channel with data quantization at the relay. To this purpose the modified Cramer-Rao (MCRB) bound is calculated, which, compared to the true Cramer-Rao bound (CRB), is a looser and computationally less complex bound that converges to the CRB in the high signal-to-noise ratios. By using a general system model for the relay channel, the obtained results can be utilized to benchmark a wide variety of systems.