On the Average Rate of HARQ-Based Quasi-Static Spectrum Sharing Networks

Spectrum sharing networks are communication setups in which unlicensed secondary users are permitted to work within the spectrum resources of primary licensees. Considering quasi-static fading environments, this paper studies the effect of hybrid automatic repeat request (HARQ) feedback on the average rate of unlicensed spectrum sharing channels. The results are obtained for different scenarios; Under both peak and average secondary user transmission power constraints, the channel average rate is determined under primary user limited received interference power conditions when there is perfect information about the interference available at the secondary user transmitter. An approximate solution for power allocation between incremental redundancy (INR) HARQ-based data retransmissions is proposed which can be applied in single-user networks as well. Then, we investigate the effect of imperfect secondary-primary channel state information on the interference-limited average rate of the secondary channel. Finally, we restudy all mentioned scenarios in the case where the data transmission is constrained to have limited outage probability. Substantial performance improvement is observed with even a single HARQ-based retransmission in all simulations

Low-bit rate feedback strategies for iterative IA-precoded MIMO-OFDM-based systems

Interference alignment (IA) is a promising technique that allows high-capacity gains in interference channels, but which requires the knowledge of the channel state information (CSI) for all the system links. We design low-complexity and low-bit rate feedback strategies where a quantized version of some CSI parameters is fed back from the user terminal (UT) to the base station (BS), which shares it with the other BSs through a limited-capacity backhaul network. This information is then used by BSs to perform the overall IA design. With the proposed strategies, we only need to send part of the CSI information, and this can even be sent only once for a set of data blocks transmitted over time-varying channels. These strategies are applied to iterative MMSE-based IA techniques for the downlink of broadband wireless OFDM systems with limited feedback. A new robust iterative IA technique, where channel quantization errors are taken into account in IA design, is also proposed and evaluated. With our proposed strategies, we need a small number of quantization bits to transmit and share the CSI, when comparing with the techniques used in previous works, while allowing performance close to the one obtained with perfect channel knowledge