Simultaneous wireless information and power transfer (SWIPT) is an emerging technology to connect and energize devices wirelessly, in the future Internet of Things (IoT) and wireless sensor networks (WSN). In this paper, we investigate two coherent detection schemes for integrated SWIPT receivers. At first, we examine a single input multiple output (SIMO) topology, with multiple rectennas at the receiver's side, i.e. MRCA scheme. Targeting to reduce the decoding complexity, we further investigate a single input single output (SISO) topology, with one receive antenna connected to multiple rectifiers, i.e. MRCE scheme. A non-linear energy harvesting (EH) model, is considered for both schemes, by taking into account the sensitivity and saturation effects of rectifiers. With the use of maximum likelihood (ML) and soft decoding, energy detection is succeeded. An asymptotic analysis is conducted for both schemes, providing upper and lower bounds for EH and information decoding, respectively. Simulation and experimental results along with theoretical analysis, validate the enhanced performance of the proposed schemes.

Adopting the concept of simultaneous wireless information and power transfer (SWIPT), applied over an integrated architecture of receiver, we propose a solution for an improved information decoder. Our research concludes to an enhanced performance with dual objective of pursuing a lower symbol error rate, while at the same time achieving the highest energy harvested in the battery. Information is conveyed by the intensity power levels of the signal, while with the use of pulse energy detection techniques, we can successfully decode it through the energy variation of the receiver. Our contribution, relies on a new sophisticated detection scheme, for non-coherent sequential detection in the integrated receiver. A Viterbi-type trellis-search algorithm, combined with selective store strategy is applied, resulting in a low-complexity, while at the same time more efficient in terms of memory requirements. Simulation results, approach the numerical ones as the observation window L → ∞, thus demonstrating that our proposed sequential decoder leads to a novel SWIPT solution with gains, in terms of SER, lower computational complexity, high energy harvested and memory efficiency.

A vision of digital and connected world is now a global strategy for 5G internet of things (IoT), targeting for high speed communication services with more capacity, lower latency, increased reliability and availability. In this paper, we assess the added value of backscatter communication in 5G IoT technology, by studying spatial modulation-based techniques, applied over a traditional multiple antenna backscatter communication system. Particularly, with backscatter we fulfill the need for wireless self-powered devices, as one of the main characteristics of 5G IoT. Furthermore, with the use of multiple antennas, we apply sophisticated techniques that enhance the overall efficiency of the backscatter communication system. Initially, we study generalized spatial modulation (GSM) and its special case of spatial modulation (SM), exploiting the antenna index as an additional source of information. With this technique, enhanced performance in terms of symbol error rate (SER) and spectral efficiency, is provided. In addition, we expand GSM in time domain, by applying Alamouti coding scheme (GSMA) in two out of the multiple available antennas. In this way, we further enhance the performance and succeed transmit diversity. Finally, analytical expressions regarding the pairwise error probability are derived and presented, while a diversity analysis is carried out for the proposed techniques. Simulation results along with theoretical bounds are provided, validating the enhanced performance of our study.