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Non-coherent (NC) schemes combined with massive antenna arrays are proposed to replace traditional coherent schemes in scenarios which require an excessive number of reference signals, since NC approaches avoid channel estimation and equalization. Differential M-ary phase shift keying is one of the most appealing NC schemes due to its implementation simplicity in realistic scenarios. However, the analytical constellation design for multiuser scenarios is intractable, as discussed in this paper. We propose to solve this problem by using optimization techniques relying on evolutionary computation. We design two approaches, namely Gaussian-approximated optimization and Monte-Carlo based optimization. They can provide both individual constellations for each user equipment and a bit mapping policy to minimize the bit error rate. We perform a complexity analysis and propose strategies for its reduction. We propose a set of constellations for different number of users and constellation sizes, and evaluate the link-level performance of some illustrative examples to verify that our solutions outperforms the existing ones. Finally, we show via simulations that NC outperforms the coherent schemes in high mobility and/or low signal-to-noise ratio scenarios. This work has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie ETN TeamUp5G, grant agreement No.813391, and from Spanish National Project IRENE-EARTH (PID2020-115323RB-C33) (MINECO/AEI/FEDER, UE). The work of O. A. Dobre has been supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC), through its Discovery program.

Under high-mobility scenarios, the traditional coherent demodulation schemes (CDS) have limited performance, because reference signals cannot effectively track the channel variations with an affordable overhead. As an alternative solution, non-coherent demodulation schemes (NCDS) based on differential modulation have been proposed. Even in the absence of reference signals, they are capable of outperforming the CDS with a reduced complexity. The literature on NCDS laid the theoretical foundations for simplified channel and signal models, often single-carrier and spatially uncorrelated flat-fading channels. This chapter explains the most recent results assuming orthogonal frequency division multiplexing (OFDM) signaling and realistic channel models.

Pilot-pouring superimposed training (PPST) is a novel channel estimation technique specially designed for cyclic block filtered multi-tone (CB-FMT), where the pilot symbols are poured into the subcarriers taking advantage of the power left unused by the data symbols. Hence, since this technique is based on superimposed training (ST) principles, the data rate is not reduced, unlike the pilot symbol assisted modulation (PSAM). Besides, it exploits a weighted average at the receiver side that is capable of minimizing the mean squared error (MSE) of the channel estimation, and then enhancing the performance of the system. However, the existing proposal on PPST is limited to the minimization of the MSE to improve channel estimation for a given power allocation factor, without solving the joint optimization of channel estimation and data detection procedures. With this aim, this work addresses the whole problem to reach the best performance for both tasks, thus taking into account also the power allocation factor in the opt where the pilot symbols are poured into the subcarriers taking advantage of the power left unused by the data symbols. Hence, since this technique is based on superimposed training (ST) principles, the data rate is not reduced, unlike the pilot symbol assisted modulation (PSAM). Besides, it exploits a weighted average at the receiver side that is capable of minimizing the mean squared error (MSE) of the channel estimation, and then enhancing the performance of the system. However, the existing proposal on PPST is limited to the minimization of the MSE to improve channel estimation for a given power allocation factor, without solving the joint optimization of channel estimation and data detection procedures. With this aim, this work addresses the whole problem to reach the best performance for both tasks, thus taking into account also the power allocation factor in the optimization process, where the spectral efficiency must be maximized through the signal-to-interference plus noise ratio (SINR). Two optimization approaches are proposed, where the first one, referred as pilot-pouring optimization (PPO), is focused on performance at the expense of a high complexity, while the second one, denoted as low-complexity PPO (LPPO), is able to trade-off between performance and execution time. Numerical results are provided in order to show the validity of our proposal, where the different optimization problems are compared in terms of SINR and execution time. This work was supported by Spanish National Projects TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE), and IRENE-EARTH (PID2020-115323RB-C33 / AEI / 10.13039/501100011033). The work of A. M. Tonello was supported by the Chair of Excellence Program of the Universidad Carlos III de Madrid.

Cyclic block filtered multi-tone (CB-FMT) is a waveform that can be efficiently synthesized through a filter-bank in the frequency domain. Although the main principles have been already established, channel estimation has not been addressed yet. This is because of assuming that the existing techniques based on pilot symbol assisted modulation (PSAM), implemented in OFDM-like schemes, can be reused. However, PSAM leads to an undesirable loss of data-rate. In this paper, an alternative method inspired by the superimposed training (ST) concept, namely pilot pouring ST (PPST), is proposed. In PPST, pilots are superimposed over data taking advantage of the particular spectral characteristics of CB-FMT. Exploiting the sub-channel spectrum, the pilot symbols are poured in those resources unused for data transmission. This spectral shaping of pilots is also exploited at the receiver to carry out channel estimation, by enhancing those channel estimates that exhibit a low data interference contribution. Furthermore, a frequency domain resource mapping strategy for the data and poured pilot symbols is proposed to enable an accurate estimation in strongly frequency-selective channels. The parameters of the proposed scheme are optimized to minimize the channel estimation mean squared error (MSE). Finally, several numerical results illustrate the performance advantages of the proposed technique as compared to other alternatives.

Superimposed training (ST) is a semiblind channel estimation technique, proposed for orthogonal frequency division multiplexing (OFDM), where training sequences are added to data symbols, avoiding the use of dedicated pilot-subcarriers, and increasing the available bandwidth compared with pilot symbol assisted modulation (PSAM). Filter bank multicarrier offset quadrature amplitude modulation (FBMC-OQAM) is a promising waveform technique considered to replace the OFDM, which takes advantage of well-designed filters to avoid the use of cyclic prefix and reduce the out-band-emissions. In this paper, we provide the expressions of the average channel capacity of the FBMC-OQAM combined with either PSAM or ST schemes, considering imperfect channel estimation and the presence of the pilot sequences. In order to compute the capacity expression of our proposal, ST-FBMC-OQAM, we analyze the channel estimation error and its variance. The average channel capacity is deduced considering the noise, data interference from ST, and the intrinsic self-interference of the FBMC-OQAM. Additionally, to maximize the average channel capacity, the optimal value of data power allocation is also obtained. The simulation results confirm the validity of the capacity analysis and demonstrate the superiority of the ST-FBMC-OQAM over existing proposals.

Proceeding of: 12th IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing, (CSNDSP), 20-22, July 2020, (Online). The performance of communication systems dependson the choice of constellations, designed in an end-to-endmanner. In case of a mathematical intractability, either becauseof complexity or even lack of channel model only sub-optimal solutionscan be provided with an analytical approach. We presentend-to-end learning, a recent technique in communications tolearn optimal transmitter and receiver architectures based ondeep neural networks (DNNs) architectures. We discuss cases inwhich this technique has been used to design constellations inwhich channel model intractability repressed from a mathematicalanalysis. This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie ETN TeamUp5G, grant agreement No. 813391, and from the Spanish National Project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE).

Massive multiple-input multiple-output (MIMO) combined with orthogonal frequency division multiplexing (OFDM) are key techniques in the evolution of mobile communications. In coherent demodulation schemes, the computation of zero-forcing (ZF) equalizers can be very complex, in particular when the number of subcarriers and/or antennas is high. In the context of massive MIMO, we propose the combination of using Neumann series (NS) as a low-complexity approximation to obtain the matrix inversions with the interpolation of the inverted matrix, that, to the best of our knowledge, have never been analyzed in this context. We will show that when the number of antennas at the base station (BS) is larger than the number of users, our proposed scheme has the same performance as the traditional one, with lower complexity. We also provide some numerical results in order to verify our analysis.

Proceedings of: 2019 IEEE International Conference on Communications Workshops (ICC Workshops), 20-24 May 2019, Shanghai, China. Millimeter-Wave (mm-Wave) and very large multiple antenna systems (VLMAS) are two key technologies in the deployment of Fifth Generation (5G) mobile communication systems. In order to exploit all the benefits of VLMAS, spatial and temporal (ST) features must be estimated and exploited to compute the precoding/decoding matrices. In the literature, a practical channel estimation approach is proposed by assuming that the spatial features are completely unknown, leading to non-parametric estimation in which antenna array calibration is not required. Additionally, when the signal-to-noise ratio (SNR) is not so high, a low-rank (LR) version of the estimated channel is proposed that provides better performance than the full-rank (FR) one in terms of bias-variance trade-off in the mean squared error (MSE). However, previous work assumes that spatial and temporal characteristics of the channel can be estimated separately. Then, the performance is degraded in realistic channels. In this paper, we propose an alternative way to characterize the FR estimated channel using a joint ST covariance matrix, combined with a low-complexity semi-parametric spatial response and delay estimation technique. Moreover, we propose an automatic rank-selector (ARS) based on the MSE in order to provide the best LR channel estimation for each scenario. Numerical results show that the proposed technique outperforms existing approaches in the literature. This work has been partly funded by projects TERESA-ADA (TEC2017-90093-C3-2-R)(MINECO/AEI/FEDER, UE) and the fellowship of University Carlos III of Madrid under the program "Ayudas para la Movilidad del Programa Propio de Investigacion" granted to K. Chen-Hu

Proceedings of: ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 20-24 may, 2019, Shanghai. Massive multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are wireless technologies adopted by the Fifth Generation (5G) of mobile communications. The channel estimation and pre/postequalization processes in coherent detection schemes for massive MIMO-OFDM are a challenging task, where several issues are faced, such as pilot contamination, channel calibration, matrix inversions, among others. Moreover, they increase the energy consumption and latency of the system. A non-coherent technique relying on DPSK constellation has been proposed for a singlecarrier scheme, assuming flat-fading. In our paper, we extend this technique to be combined with OFDM, where the channel is doubly dispersive (time and frequency). We will show that the differential modulation can be performed either in the time or frequency domain, where the latter suffers from an additional phase rotation, which should be estimated and compensated. We provide the analytical expression of the signal-to-interferenceand-noise ratio (SINR) for both cases, and we show numerical results in order to verify our analysis. This work has been funded by project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE).

Proceedings of: 2018 IEEE 87th Vehicular Technology Conference (VTC Spring) The Fifth Generation of mobile communications (5G) is being standardized based on Orthogonal Frequency Division Multiplexing (OFDM) waveforms. The high out-of-band emissions (OBE) are one of the main drawbacks of OFDM, which reduce the spectral efficiency and force us to leave wide guard bands. A strong candidate to replace OFDM is filtered-OFDM (f-OFDM) which solves the mentioned issue and keeps the backward compatibility. However, it increments the inter-symbol interference (ISI) due to the use of digital filters. We propose a new technique to overcome this problem. It is based on shaping the power of OFDM by the scheduler according to the demanded rates and channel quality of the users, while decreasing the OBE and avoiding the ISI increase. The interference generated by our proposed technique on a narrow-band signal based on legacy OFDM is analyzed. Moreover, simulations are performed to validate the theoretical analysis and some examples of implementation are also provided in the context of 5G evolution. This work has been partly funded by projects MACHINE (TSI-100102-2015-17), TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE) and ELISA (TEC2014-59255-C3-3-R).

The Fifth Generation of mobile communications (5G) is being standardized in order to reach higher data rates and deploy new services. In this frame, researchers are looking for possible waveforms to improve the air interface. Orthogonal Frequency Division Multiplexing (OFDM) has high Out-of-Band Emissions (OBE) which force us to leave wider guard bands, reducing so the spectral efficiency. Recently, we have proposed the Power Adapted-OFDM which is capable of fulfilling the requirements of 5G and avoids the main issues of other proposed candidates. OpenAir Interface (OAI) is a powerful and flexible wireless technology platform based on the Long-Term Evolution (LTE) ecosystem, which offers the possibility of evaluating the effects of introducing a new technology on the entire mobile communication system. In this paper, we will evaluate and show the performance of the proposed technique using the OAI.

Filter bank multicarrier offset quadrature amplitude modulation (FBMC) has advantages over the well-known orthogonal frequency division multiplexing due to its improved time-frequency efficiency. However, the self-interference of FBMC is an important issue in order to perform the channel estimation. To face this interference in FBMC, several pilot-based schemes have been proposed, but with a high complexity. We propose a novel approach, simple yet effective, based on the use of continuous pilot sequences (CPS) in FBMC. Our scheme considers an adequately designed pilot sequence, taking into account the self interference, combined with a low-complexity channel estimation method that has a better performance in terms of mean squared error (MSE) and symbol error rate than previous methods proposed in the literature. Additionally, we also introduce burst pilot sequences, which have the same benefits of CPS while they reduce the number of required pilots and, thus, increase the available resources for data transmission. Moreover, we derive an analytical model to theoretically characterize the MSE of our proposed schemes. Simulation results have confirmed the validity of these theoretical expressions since their values match perfectly. This work was supported in part by the Spanish National Projects ELISA under Grant TEC2014-59255-C3-3-R, in part by the TERESA-ADA under Grant TEC2017-90093-C3-2-R (MINECO/AEI/FEDER, UE), and in part by the MACHINE under Grant TSI-100102-2015-17, and also in part by the National Secretary of Science, Technology and Innovation SENESCYT (Ecuador).

Proceedings of: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall) Wireless broadband communication systems are always requiring higher data rates. In order to achieve this goal, we should provide advanced schemes which are capable of improving the spectral efficiency and reusing, in a better way, the available radio spectrum resources. Filter Bank Multi-Carrier Offset Quadrature Amplitude Modulation (FBMC-OQAM) combined with Superimposed Training (ST) is a promising technique with a very high spectral efficiency. This improvement is due to the low out-of-band emissions of FBMC-OQAM, because it uses a well-designed prototype filter, and the lack of dedicated pilot tones owing to ST scheme. However, this combination is not straightforward due to the appearance of the self-interference at receiver side in FBMC-OQAM. In this paper, we provide a novel channel estimation which is capable of dealing with this self-interference in the context of combining these two techniques. This work has been partly supported by Spanish National Projects ELISA (TEC2014-59255-C3-3-R) and MACHINE (TSI-100102-2015-17); and also by National Secretary of Science, Technology and Innovation SENESCYT Ecuador.

Proceeding of: 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Valencia, 4-8 septiembre, 2016. Machine type communications (MTC) have been growing significantly in recent years and this tendency is foreseen to be kept in the near future playing an increasingly important role in the industry. The signals used for MTC will coexist with the current and next generation cellular systems. Therefore it is of interest to study how they can perform jointly and the viability of coexistence of signals from both systems. We focus in one of the new waveforms being discussed for 5G, namely on filtered-OFDM (f-OFDM), along with traditional OFDM. The interference is analysed for both types of signals and the expression of the SINR is found allowing us to compare the behavior of OFDM and f-OFDM in these circumstances. Some simulations are shown to validate the theoretical analysis and explore some foreseen MTC scenarios. This work has been partly funded by projects MACHINE (TSI-100102-2015-17) and ELISA (TEC2014-59255-C3-3-R).

Proceedings of: Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016 IEEE We are witnessing a revolution in wireless technology where Light Fidelity (LiFi) emerges as one potential candidate. In this paper we present a LiFi prototype that allows us to verify the feasibility of deploying this technology. The prototype is based on two Spartan 6 FPGAs and uses a Light Emitting Diode (LED) to transport the information through amplitude changes of the light. The receiver uses a low dark current PIN photodiode. We describe the system design, the receiver algorithms and the measurement set-up. We present some measurements where in a Line of Sight (LOS) channel the received pulses are shown to match the transmitted ones. This work has been partly funded by the Company UVAX-Concepts, within Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica 2013-2016 (TSI-100502-2013-024) and ELISA project (TEC2014-59255-C3-3-R). The authors would like to thank this support.

The Reconfigurable Intelligent Surface (RIS) constitutes one of the prominent technologies for the next generation of wireless communications. It is envisioned to enhance the signal coverage in cases when the direct link of the communication is weak. Recently, beam training based on codebook selection is proposed to obtain the optimized phase configuration of the RIS. After that, the data is transmitted and received by using the classical coherent demodulation scheme (CDS). This training approach is able to avoid the large overhead required by the channel sounding process, and it also circumvents complex optimization problems. However, the beam training still requires the transmission of some reference signals to test the different phase configurations of the codebook, and the best codeword is chosen according to the measurement of the received energy of the reference signals. Then, the overhead due to the transmission of reference signals reduces the spectral efficiency. In this paper, a zero overhead beam training for RIS is proposed, relying on data transmission and reception based on non-CDS (NCDS). At the BS, the received differential data can also be used for the determination of the best beam for the RIS. Therefore, the efficiency of the system is significantly enhanced since reference signals are fully avoided. After choosing the best codebook, NCDS is still more suitable to transmit information for high mobility scenarios as compared to the classical CDS. Analytical expressions for the Signal-to-Interference and Noise Ratio (SINR) for the non-coherent RIS-empowered system are presented. Moreover, a detailed comparison between the NCDS and CDS in terms of efficiency and complexity is also given. The extensive computer simulation results verify the accuracy of the presented analysis and showcase that the proposed system outperforms the existing solutions., Comment: Accepted by IEEE Access 2022

Pilot symbol assisted modulation (PSAM) is widely used to obtain the channel state information (CSI) needed for coherent demodulation. It allows the density of pilot symbols to be dynamically chosen depending on the channel conditions. However, the insertion of pilots reduces the spectral efficiency, more severely when the channel is highly time-variant and/or frequency-selective. In these cases a significant amount of pilots is required to properly track the channel variations in both time and frequency dimensions. Alternatively, non-coherent demodulation does not require any CSI for the demodulation independently of the channel conditions. For the particular case of up-link (UL) based on massive single input -multiple output (SIMO) combined with orthogonal frequency division multiplexing (OFDM), we propose to replace the traditional reference signals of PSAM by a new differentially-encoded data stream that can be non-coherently detected. The latter can be demodulated without the knowledge of the CSI and subsequently used for the channel estimation. We denote our proposal as hybrid demodulation scheme (HDS) because it exploits both the benefits of a coherent demodulation scheme (CDS) and a non-coherent demodulation scheme (NCDS) to increase the spectral efficiency. The mean squared error (MSE) of the channel estimation, bit error rate (BER), achieved throughput and complexity are analyzed to highlight the benefits of this differential data-aided channel estimation as compared to other approaches. We show that the channel estimation is almost as good as PSAM, while the BER performance and throughput are improved for different channel conditions with a very small complexity increase. This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391, and from the Spanish National Project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE).