In this paper, we present a novel resource allocation (RA) algorithm for packet Universal Filtered Multi-Carrier (UFMC) BIC-based communications, the latter being a novel modulation format possibly envisaged to be applied in 5G wireless systems. Assuming the perfect knowledge of the channel and capitalizing on the specific UFMC signal waveform, the proposed RA strategy optimizes the coding rate and bit loading within the overall bandwidth along with the per-subband power distribution. In the presence of a carrier offset and over fading selective channels, the results we obtained are twofold: i) the UFMC format reveals to be more robust than the conventional OFDM scheme; ii) the performance of the UFMC system itself is further boosted by the optimal choice of radio resources evaluated by the proposed RA algorithm

A cognitive radio scenario is considered where the signals transmitted by a secondary user (SU) are relayed by multi-antenna relays using an amplify-and-forward cooperation protocol. In this paper, the optimal power allocation and beamforming scheme is derived for the SU transmitters (SU-TXs) which minimizes the exact outage probability of the SU network with relay selection, under both a transmit power constraint and a constraint on the interference power generated at every primary user receiver. After deriving the optimal structure of the beamforming matrix, several distributed resource allocation algorithms are obtained for different levels of channel state information (CSI) at the SU-TXs: perfect CSI and imperfect CSI are considered, along with the case where only channel distribution information (CDI) is available. The numerical results show that the multi-antenna relays can significantly improve the performance of the SU network, which would otherwise be severely limited by the harsh interference constraints. Further, we also investigate how the number of relays, the number of antennas and the level of CSI impact the performance of the SU network. Finally, we point out that the proposed algorithms outperform several algorithms presented in literature.

In this paper we consider a decode-and-forward cooperative network, which is active in the same bandwidth as a primary user network. The cooperative or secondary user network applies a dynamic resource allocation algorithm to maximize its own performance while limiting the interference caused at the primary user receivers. The main contribution of this paper is the proposition of a new accurate approximation for the outage probability, which takes into account that the channel state information available at the transmitter is imperfect and outdated. The accuracy of the approximation and the performance of the resource allocation scheme are validated through numerical simulations

We propose a novel resource allocation (RA) strategy for a cognitive radio packet-oriented bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system with decode-and-forward (DF) relays. The aim of the RA is maximizing the goodput (GP) of the source-relay-destination link, which is the number of information bits correctly received at the destination node per unit of time. Therefore, we derive an accurate analytic approximation for this figure of merit, which allows us to find the optimum constellation size, code rate and energy allocation per subcarrier. Further, this expression also serves as a novel relay selection criterion. Finally, we validate the proposed RA method, and compare its performance to capacitymaximizing algorithms through numerical simulations

No abstract