Multipair Full-Duplex Relaying with Massive Arrays and Linear Processing

We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To reduce significantly the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, especially for large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as, to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5dB if the pilot power is equal to the signal power, and by 3dB if the pilot power is kept fixed, while maintaining a given quality-of-service

Buffer-Aided Relaying with Adaptive Link Selection - Fixed and Mixed Rate Transmission

We consider a simple network consisting of a source, a half-duplex DF relay with a buffer, and a destination. We assume that the direct source-destination link is not available and all links undergo fading. We propose two new buffer-aided relaying schemes. In the first scheme, neither the source nor the relay have CSIT, and consequently, both nodes are forced to transmit with fixed rates. In contrast, in the second scheme, the source does not have CSIT and transmits with fixed rate but the relay has CSIT and adapts its transmission rate accordingly. In the absence of delay constraints, for both fixed rate and mixed rate transmission, we derive the throughput-optimal buffer-aided relaying protocols which select either the source or the relay for transmission based on the instantaneous SNRs of the source-relay and the relay-destination links. In addition, for the delay constrained case, we develop buffer-aided relaying protocols that achieve a predefined average delay. Compared to conventional relaying protocols, which select the transmitting node according to a predefined schedule independent of the link instantaneous SNRs, the proposed buffer-aided protocols with adaptive link selection achieve large performance gains. In particular, for fixed rate transmission, we show that the proposed protocol achieves a diversity gain of two as long as an average delay of more than three time slots can be afforded. Furthermore, for mixed rate transmission with an average delay of $E{T}$ time slots, a multiplexing gain of $r=1-1/(2E{T})$ is achieved. Hence, for mixed rate transmission, for sufficiently large average delays, buffer-aided half-duplex relaying with and without adaptive link selection does not suffer from a multiplexing gain loss compared to full-duplex relaying.Comment: IEEE Transactions on Information Theory. (Published

On the optimization of distributed compression in multirelay cooperative networks

In this paper, we consider multirelay cooperative networks for the Rayleigh fading channel, where each relay, upon receiving its own channel observation, independently compresses it and forwards the compressed information to the destination. Although the compression at each relay is distributed using Wyner-Ziv coding, there exists an opportunity for jointly optimizing compression at multiple relays to maximize the achievable rate. Considering Gaussian signaling, a primal optimization problem is formulated accordingly. We prove that the primal problem can be solved by resorting to its Lagrangian dual problem, and an iterative optimization algorithm is proposed. The analysis is further extended to a hybrid scheme, where the employed forwarding scheme depends on the decoding status of each relay. The relays that are capable of successful decoding perform a decode-and-forward (DF) scheme, and the rest conduct distributed compression. The hybrid scheme allows the cooperative network to adapt to the changes of the channel conditions and benefit from an enhanced level of flexibility. Numerical results from both spectrum and energy efficiency perspectives show that the joint optimization improves efficiency of compression and identify the scenarios where the proposed schemes outperform the conventional forwarding schemes. The findings provide important insights into the optimal deployment of relays in a realistic cellular network