In this paper, intelligent reflecting surfaces (IRSs) are exploited for simultaneous wireless information and power transfer. In the considered setup, the IRS, illuminated by a power transmitter, provides power to integrated sensors through energy harvesting while simultaneously transmitting information through differential permutation-based coding. The problem of allocating the IRS elements to either information or power transmission is studied, highlighting the tradeoff between the system throughput and the harvested power. The conducted performance analysis emphasizes the suitability of using IRSs in a SWIPT scenario without the need for cabled links or channel state information.

In this paper, we study the tradeoffs between complexity and reliability for decoding large linear block codes. We show that using artificial neural networks to predict the required order of an ordered statistics based decoder helps in reducing the average complexity and hence the latency of the decoder. We numerically validate the approach through Monte Carlo simulations.

This paper presents an antenna selection and two bit allocation methods for general spatial modulation, all based on channel state information. The proposed antenna selection method maximizes the Euclidean distance between the possible antenna selections in order to decrease the bit error rate. The bit allocation methods aim at determining the neighboring symbols and minimizing the Hamming distance in between them. In some scenarios, we show, through Monte Carlo simulations, that the presented methods have lower computational complexity and perform better than the existing approaches.

In this paper, we study the characteristics of dominant interference power with directional reception in a random network modelled by a Poisson Point Process. Additionally, the Laplace functional of cumulative interference excluding the n dominant interferers is also derived, which turns out to be a generalization of omni-directional reception and complete accumulative interference. As an application of these results, we study the impact of directional receivers in random networks in terms of outage probability and error probability with queue length constraint.

For spatial modulation (SM) systems that utilize multiple transmit antennas/patterns with a single radio front-end, we propose a learning approach to predict the average symbol error rate (SER) conditioned on the instantaneous channel state. We show that the predicted SER can he used to lower the average SER over Rayleigh fading channels by selecting the optimal codebook in each transmission instance. Further by exploiting that feedforward artificial neural networks (ANNs) trained with a mean squared error (MSE) criterion estimate the conditional a posteriori probabilities, we maximize the expected rate for each transmission instance and thereby improve the link spectral efficiency.

In this paper, we present a modulation design based on Spatial Modulation for the uplink in IoT applications. The proposed modulation design uses a Tabu search based deterministic heuristic to adapt the modulation link based on channel information fed back by the receiver. Our approach allows adaptivity to rate and energy constraints. We numerically validate the proposed method on a scenario with full channel state information available at the transceiver, showing clear performance gains compared to simpler heuristics and channel independent codebook designs.

In this paper, we analyse different spectrally efficient waveforming modulations under the framework of Gabor analysis. We derive a channel adaptive pulse design paradigm for such modulations under Maximum Likelihood (ML) detection at the receiver. The proposed pulse design is tested on a simulation scenario with high self-interference and compared with existing pulses at different spectral densities.

In this paper we have proposed clock error mitigation from the measurements in the scheduled based self localization system. We propose measurement model with clock errors while following a scheduled transmission among anchor nodes. Further, RLS algorithm is proposed to estimate clock error and to calibrate measurements of self localizing node against relative clock errors of anchor nodes. A full-scale experimental validation is provided based on commercial off-the-shelf UWB radios under IEEE-standardized protocols.