Lower bounds on the estimation performance in low complexity quantize-and-forward cooperative systems

Cooperative communication can effectively mitigate the effects of multipath propagation fading by using relay channels to provide spatial diversity. A relaying scheme suitable for half-duplex devices is the quantize-and-forward (QF) protocol, in which the information received from the source is quantized at the relay before being forwarded to the destination. In this contribution, the Cramer-Rao bound (CRB) is obtained for the case where all channel parameters in a QF system are estimated at the destination. The CRB is a lower bound (LB) on the mean square estimation error (MSEE) of an unbiased estimate and can thus be used to benchmark practical estimation algorithms. Additionally, the modified Cramer-Rao bound (MCRB) is also presented, which is a looser but computationally less complex bound. An importance sampling technique is developed to speed up the computation of the MCRBs, and the MSEE performance of a practical estimation algorithm is compared with the (M)CRBs. We point out that the parameters of the source-destination and relay-destination channels can be accurately estimated but that inevitably the source-relay channel estimate is poor when the instantaneous SNR on the relay-destination channel is low; however, in this case, the decoder performance is not affected by the inaccurate source-relay channel estimate

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

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