PRACTICAL QUANTIZE-AND-FORWARD SCHEMES FOR THE FREQUENCY RELAY CHANNEL

International audienceWe consider static and quasi-static relay channels in which the source-destination and relay-destination signals are assumed to be orthogonal and thus have to be recombined at the destination. We propose cheap relaying schemes that are optimized from the knowledge of the signal-to-noise ratios (SNRs) of the source-relay and relay-destination channels at the relay. For this purpose the scheme under investigation is assumed to be scalar and have to minimize the mean square error between the source signal and its reconstructed version at the destination. We propose a quantize-and-forward (QF) scheme, which is a generalization of techniques based on joint source-channel coding. To further improve the receiver performance when the source-relay SNR is relatively poor we propose a Maximum Likelihood detector (MLD) designed for the QF protocol

H2-ARQ-relaying: spectrum and energy efficiency perspectives

In this paper, we propose novel Hybrid Automatic Repeat re-Quest (HARQ) strategies used in conjunction with hybrid relaying schemes, named as H2-ARQ-Relaying. The strategies allow the relay to dynamically switch between amplify-and-forward/compress-and-forward and decode-and-forward schemes according to its decoding status. The performance analysis is conducted from both the spectrum and energy efficiency perspectives. The spectrum efficiency of the proposed strategies, in terms of the maximum throughput, is significantly improved compared with their non-hybrid counterparts under the same constraints. The consumed energy per bit is optimized by manipulating the node activation time, the transmission energy and the power allocation between the source and the relay. The circuitry energy consumption of all involved nodes is taken into consideration. Numerical results shed light on how and when the energy efficiency can be improved in cooperative HARQ. For instance, cooperative HARQ is shown to be energy efficient in long distance transmission only. Furthermore, we consider the fact that the compress-and-forward scheme requires instantaneous signal to noise ratios of all three constituent links. However, this requirement can be impractical in some cases. In this regard, we introduce an improved strategy where only partial and affordable channel state information feedback is needed

Compress-and-forward cooperative MIMO relaying with full channel state information

Postprint (author’s final draft

Low-complexity iterative soft detection for LDPC coded multi-relay channels

Next generation wireless communication applications require reliable transmission of data at high data rates and a guarantee of quality-of-service over wireless links. However, degradations inherent in wireless channels, such as multipath fading, shadowing, path loss, and noise lead to reduction in the communication capacity and range significantly. One way to combat these adverse limitations is to employ spatial diversity, which can be achieved, for example, by transmitting independent copies of the signal over relay nodes, resulting in improvements in the transmission rates, reliability, and the capacity of the channel under pre-mentioned detrimental effects. In addition to exploiting diversity, the capacity of the channel can be further increased by employing an error correction code such as low-density parity check (LDPC) codes and turbo codes, etc. Throughout this thesis, we consider LDPC coded full-duplex multi-relay channels using Estimate and Forward (EF) and Decode and Forward (DF) protocol. We focus on designing optimal and sub-optimal iterative soft detectors. Although the use of multirelaying improves the channel reliability, the performance of the system is degraded because of the interference caused by multiple received signals coming from all relay nodes. To reduce the effect of the interference, maximum a posteriori (MAP) detector can be employed. Unfortunately, the complexity of the MAP detector grows exponentially as the number of relays increases. In the literature, two computationally efficient sub-optimal detectors have been proposed based on Taylor expansion or Central Limit Theorem (CLT) assumption to alleviate this problem. However, we find out that the correlation between intrinsic and extrinsic information stemming from these suboptimal detectors is very high, and this correlation degrades the detector performance. To remedy that, in this thesis, we developed two new detectors: Soft Decorrelating Detection-Taylor (SODED-Taylor) and Soft Decorrelating Detection-CLT (SODEDCLT), which improves the performance of sub-optimal detectors about 0.8 dB - 1 dB