This paper focuses on communication, radar search, and tracking task scheduling in multi-cell integrated sensing and communication (ISAC) networks under quality-of-service constraints. We propose a medium access control framework that multiplexes these tasks while optimizing radar scan patterns through an interference-aware scheduling algorithm. Specifically, the proposed framework employs time-domain task scheduling and beam selection, formulated as an assignment problem, to mitigate inter-task and inter-cell interference, respectively. Simulations show that our solution guarantees target communication throughput, sensing target detection probability, and sensing signal-to-interference-plus-noise ratio with improved resource efficiency over baseline schemes, highlighting the benefits of coordinated scheduling in multi-cell ISAC.

Frequency-shifting reconfigurable intelligent surfaces (FS-RISs) represent a novel operation mode relying upon metamaterials capable of shifting the carrier frequency of transmitted signals. While the technology is still not mature for wider deployment, previous work has revealed its significant potential for improvements in wireless communication. This work expands the application domain of FS-RIS towards localization within cellular networks operating at sub-6 GHz. The FS-RIS upconverts signals transmitted by the base station to the millimetre-wave spectrum, redirecting them to the user and enabling precise position estimation through narrow, highly directive beams. To eliminate the overhead associated with traditional reference symbols, a superimposed training (ST) scheme is employed. This novel approach achieves accurate localization using only a single FS-RIS, similar to existing solutions based on multiple base stations or traditional RISs. The derived Cramér-Rao lower bound (CRLB) demonstrates that the proposed ST scheme surpasses the performance of conventional regular pilot approaches in localization accuracy while maintaining the data rate. Simulation results further validate the proposed method, showcasing significant performance gains regarding bit-error rate (BER) and position estimation error. These findings underscore the transformative potential of FS-RISs in enhancing spectrum utilization, optimizing interference management, and advancing localization applications in next-generation networks.

Orthogonal time-frequency space (OTFS) is a promising waveform for future Sixth Generation (6G) networks and beyond, offering robustness to high-mobility scenarios and enabling seamless integration of sensing and communication services by operating in the delay-Doppler (DD) domain. Reliable channel estimation is essential for both functions; however, conventional embedded-pilot (EP) schemes sustain high pilot overhead and an increased peak-to-average power ratio (PAPR). Superimposed training (ST) methods have been proposed as an alternative to reduce these limitations, since pilots and data symbols share the same DD resources. Nevertheless, existing ST-based techniques typically depend on computationally expensive algorithms or exhibit degraded communication and sensing performance. To overcome these restrictions, this work introduces a novel low-power superimposed pilot design, called sunscape pattern, and a corresponding ST-based channel estimation algorithm specifically tailored to this structure. The core design principle of the sunscape pattern is to distribute pilot energy following a structured layout in the DD domain that resembles a seascape with a sun over the sea. The sun enables accurate delay and Doppler detection (both integer and fractional), while the sea inherently supports interference averaging between pilot and data components, thereby mitigating self-interference and noise without requiring computationally expensive iterative interference cancellation. Simulation results validate the proposed scheme. They show that it achieves accurate channel estimation and reliable DD-domain detection with low computational complexity and manageable PAPR, outperforming existing approaches in both communication and sensing performance.

In this work, we propose a novel multi-user multiplexing technique for the uplink of non-coherent massive MIMO systems working under Rician fading channel conditions. Our approach eliminates the need for reference signals, enhancing spectral efficiency. Furthermore, by exploiting the estimated angle of Arrival (AoA), the proposed method significantly increases the number of users that can be simultaneously multiplexed compared to existing non-coherent massive MIMO solutions. Theoretical analysis and numerical evaluations validate the effectiveness of the proposed technique, demonstrating superior performance in terms of symbol error rate (SER) and signal to interference and noise ratio (SINR). These results highlight the practicality, scalability, and strong potential of our approach for next-generation non-coherent massive MIMO systems, making it a compelling candidate for future 6G networks.

Integrated sensing and communications (ISAC) is a new feature to be deployed in the evolution of the Sixth Generation (6G) of mobile networks. Currently, this service is planned to use the recently introduced positioning reference signal (PRS) at the expense of further sacrificing the data rate. In this work, we propose the use of a superimposed training (ST)-based simultaneous channel estimation and sensing via the superposition of a pilot Zadoff-Chu (ZC) sequence on the orthogonal frequency division multiplexing (OFDM). The proper design of the parameters of the ZC sequence and the use of matched filtering at the receiver significantly improve the quality of the channel estimates and enable accurate detection of the targets. The ZC pilot signal shares all time-frequency-space resources, thereby achieving zero pilot overhead and eliminating the need for any resources specifically dedicated to reference signals. The analysis and numerical results confirm that the proposed design achieves low-complex and accurate channel estimation and sensing, simplifying and enhancing the implementation of ISAC for 6G applications.

Frequency-shifting reconfigurable intelligent surfaces (FS-RISs) can be developed using a new generation of meta-materials that shift the original frequency spectrum of sent signals, it is also known as frequency conversion. Their application in wireless communications and localization remains in the early stages of development. This work proposes the FSRIS to provide localization services in an existing cellular network operated at sub- 6 GHz. It can up-convert the signal transmitted by the base station (BS) to the millimetre Wave and forward it to the user, allowing this to estimate its position thanks to the use of narrow directive beams. The proposed method significantly outperforms the existing solution based on multiple BSs in terms of the Cramér-Rao lower bound, which is analytically derived. An efficient data-aided beam-sweeping is provided to reduce the beam-training delay at FS-RIS without sacrificing the data rate. This work introduces a novel approach to utilizing FS-RIS in wireless systems, with the potential to reshape how we view spectrum and interference management, paving the way for more efficient communication and localization applications.

Advances in communication technologies, such as cell-free massive multi-input multiple-output architecture and edge computing, are expected to support diverse heterogeneous service requirements in industrial use cases. However, the diverse communication demands of Industry 4.0 use cases make it essential to efficiently manage both radio and computational resources. This paper introduces a novel approach that addresses these challenges through a two-step sequential optimization process. First, we propose a genetic algorithm-based radio resource allocation scheme from a scheduling perspective. A second subproblem concerning computational resource allocation is also addressed sequentially. The numerical results demonstrate that our proposed algorithm significantly improves latency compliance and effectively reduces the percentage of packets that violate deadline constraints. Considering services with small packets and strict latency constraints, the proposed scheme achieves gains of 98.5% and 99.5% compared to the benchmarking schemes. Furthermore, the proposed solution has shown great adaptability to varying latency requirements and traffic with respect to state-of-the-art schemes.

A reconfigurable intelligent surface (RIS) is commonly made of low-cost passive and reflective meta-materials with excellent beam steering capabilities. It is applied to enhance wireless communication systems as a customizable signal reflector. However, RIS can also be adversely employed to disrupt the existing communication systems by introducing new types of vulnerability to the physical layer. We consider the RIS-In-The-Middle (RITM) attack, in which an adversary uses RIS to jeopardize the direct channel between two transceivers by providing an alternative one with higher signal quality. This adversary can eavesdrop on all exchanged data by the legitimate users, but also perform a false data injection to the receiver. This work devises anti-attack techniques based on a non-reciprocal channel produced by a defensive RIS (D-RIS). The proposed precoding and combining methods and the channel estimation procedure for a non-reciprocal link are effective against potential adversaries while keeping the existing advantages of the RIS. We analyse the robustness of the system against attacks in terms of achievable secrecy rate and probability of detecting fake data. We believe that this defensive role of RIS can be a basis for new protocols and algorithms in the area.

The novel frequency-shifting reconfigurable intelligent surface (FS-RIS) is built by a new generation of meta-materials, which can perform an operation that changes the frequency spectrum of the originally transmitted signal. In this work, we exploit the FS-RIS to fight against the RIS-In-The-Middle (RITM) attack, in which an adversary uses a RIS to replace the direct channel between two legitimate transceivers. The FS-RIS can prevent not only the eavesdropping of all exchanged data by legitimate users but also avoid the false data injection to the receiver by an adversary RIS. This work devises anti-attack techniques based on a non-reciprocal channel produced by a defensive FS-RIS. The proposed combination of precoding/combining and subcarrier shifting procedures for a non-reciprocal link are robust against potential adversaries while keeping the existing advantages of the RIS. We analyse the robustness of the system against attacks in terms of achievable secrecy rate and probability of detecting fake data. We believe that this defensive role of RIS can be a basis for new protocols and algorithms in the area.

The novel frequency shifting reconfigurable intel-ligent surface (FS-RIS) is built by a new generation of meta-materials and circuits, which is able to perform an operation that changes the frequency spectrum of the signal that was originally transmitted. The use of this FS- RIS for communication is still in its infancy. In this work, a millimeter wave (mmWave) communication link aided by FS-RIS is proposed. The FS-RIS is able to down-convert the carrier frequency of the mm Wave signal and spread the control information to the cell by using a more reliable and stable link, due to the fact that lower bands have a lower attenuation. A novel multi-frequency beam-management procedure (BMP) relying on FS-RIS is given. The proposed method is faster than existing methods since it makes use of wider beams without suffering from range penalization thanks to the better propagation in sub-6 GHz bands, unlike the hierarchical BMP. Overall, this paper provides a new way to exploit FS-RIS in wireless communications, which has the potential to change the way we look at spectrum and interference management.

The reflective intelligent surface (RIS) that is com-monly considered has linear properties and does not change the frequency of the impinging signal. This is different for the emerging RIS designs, capable of doing non-linear operations on the reflected signal. We show how nonlinear RIS operation can significantly reduce the overhead for channel estimation and localization. We treat communication and sensing for cyclic-prefixed orthogonal frequency-division multiplexing (OFDM)-based system. Introducing controllable artificial Doppler-shifts through non-linear RISs enables identification of the propagation path by the frequency shift. In this way, both the direct path and multiple RIS-assisted paths can be estimated by transmission of a single OFDM-symbol. Thus, with only a minimal penalty in terms of channel estimation accuracy, this scheme achieves performance that for linear RISs would require coding across multiple OFDM-symbols. This paper considers the linear minimum mean squared error (LMMSE) channel estimator and presents four different methods to choose the pilot sequence and the artificial Doppler-shifts, in order to minimize the mean squared error (MSE) of the channel estimation.

Frequency shifting-reconfigurable intelligent surfaces (FS-RISs) can be built by a new generation of meta-materials and circuits, which can perform an operation that changes the original frequency spectrum of the transmitted signal. Its exploitation for wireless communications is still in its infancy. In this work, a millimetre wave (mmWave) cellular network aided by FS-RIS is proposed to satisfy the new challenging communication services. The FS-RIS is able to down-convert the carrier frequency of the mmWave signal and spread the control information to the cell by using a more reliable and stable link, relying on better propagation within the lower bands, and a novel multi-frequency beam-management procedure is given. The proposed method can rapidly discover all users in the entire cell by using different sizes of beams. It avoids range penalization due to the better propagation in sub-6 GHz bands, unlike the hierarchical BMP. Additionally, the proposed technique only requires one base station (BS), and hence the delay overhead caused by the information exchange among several BSs is fully avoided, unlike the case of coordinated multi-point (CoMP). Overall, this paper provides a new way to exploit FS-RIS in wireless systems, which can potentially change the way we look at spectrum and interference management for the efficient exploitation of communication applications.

Superimposed training (ST) is one of the most appealing channel estimation techniques for orthogonal frequency division multiplexing (OFDM), to be possibly exploited in the 6G. The data and pilot symbols are sharing the same time and frequency resources, and the overhead is significantly reduced. Besides, the superimposed pilots can be also used for the reduction of the peak-to-average power ratio (PAPR). However, joint channel estimation and PAPR reduction procedures have never been addressed. In this work, a novel scheme denoted as dual layers-superimposed training (DL-ST) is proposed for this joint purpose. The training sequence (TS) of the first layer is targeted to perform channel estimation, while the TS of the second layer is designed for PAPR reduction and is made transparent to the first one. Both layers can be independently processed, which implies a reduced complexity. To verify the performance of the proposed technique, the analytical expression of the channel estimation mean squared error (MSE) is derived. Finally, several numerical results further illustrate the performance of the proposal, showing how the MSE is improved while significant PAPR reductions are attained with negligible complexity.

Constant envelope orthogonal frequency division multiplexing (CE-OFDM) is a multi-carrier waveform with 0 dB peak-to-average power ratio (PAPR). This property enables the exploitation of multi-carrier waveforms with non-linear power amplifiers, avoiding the undesirable clipping effects. However, the existing channel estimation techniques designed for OFDM cannot be reused, since the use of a phase modulator makes CE-OFDM a non-linear waveform. Previous works assumed that the channel estimation process relies on the transmission of preambles, and the data symbols are equalized using a frequency domain equalizer (FDE). To avoid the overhead induced by preambles, a phase-domain injected training (PIT) is proposed, where the pilot sequence is embedded in the phase dimension of the data symbols. This novel approach does not waste time and/or frequency resources as in preamble-based schemes. Moreover, it does not require additional power for the training. The received symbols are averaged with a dual procedure, and owing to the particular structure of CE-OFDM, the channel estimates are recovered. Also, the analytical expression of the channel estimation mean squared error (MSE) is derived. Finally, several numerical results illustrate the performance of the proposal, showing that the MSE, bit error rate (BER) and achievable rate are improved, as compared to the existing works.

The Reconfigurable Intelligent Surfaces (RIS) constitute one of the prominent technologies for the next generation of wireless communications. They are mainly envisioned to efficiently enhance the signal coverage in cases where the direct communication link is weak or obstructed. Recently, beam training based on codebook selection has been proposed as a low-latency means for tuning the RIS phase profile according to a desired performance metric. However, it requires the transmission of reference signals to measure the performance with different RIS phase configurations available in the codebook, which reduces the spectral efficiency. In this paper, we consider the uplink of a Multiple-Input Signal-Output (MISO) communication system with Orthogonal Frequency-Division Multiplexing (OFDM) and present a novel scheme for simultaneous RIS phase configuration and data transmission. The proposed scheme is based on non-coherent differential modulation, which is deployed both in the beam training and the data transmission phases. In the former phase, it also enables energy measurement for the determination of the best RIS phase profile. Then, in the latter phase, a higher throughput can be established through the high gain reflective link. Our numerical results showcase that our proposal can double the system throughput with lower complexity, as compared to the generic state-of-the-art approach.

A novel time division duplex massive MIMO approach based on performing a blind channel estimation in the uplink using differentially encoded data and a precoding in the downlink, also with differentially encoded data, is proposed. In this system, the use of any type of explicit pilot data is completely avoided while maintaining spatial multiplexing capabilities in the downlink. We perform an analysis of the full system in terms or signal-to-interference-and-noise ratio (SINR) for the uplink and the downlink. The performance of the channel estimation using differentially encoded data is also analyzed, since it affects the performance of the downlink data transmission. A simple strategy to allocate the different users in an OFDM grid is proposed. The analysis is corroborated via numerical results and the proposed scheme is shown to outperform its coherent counterpart.

In this work, a spike-QAM, a regular QAM constellation where one to four of the elements with the largest amplitudes are placed further from the center, is proposed as the optimum constellation that minimizes the ratio of the symbol-error-rate (SER) to peak-to-average-power-ratio (PAPR) in simultaneous-wireless-information-and-power-transfer (SWIPT) applications. This constellation is capable of maximizing the SER performance for a given design PAPR, or maximize the PAPR given a SER performance. The relationship between these parameters is defined. An approximation to the SER performance is given for the spike-QAM in AWGN channels and it is demonstrated to be valid via numerical simulations.

Reflecting Surfaces (RSs) are being lately envisioned as an energy efficient solution capable of enhancing the signal coverage in cases where obstacles block the direct communication from Base Stations (BSs), especially at high frequency bands due to attenuation loss increase. In the current literature, wireless communications via RSs are exclusively based on traditional coherent demodulation, which necessitates the estimation of accurate Channel State Information (CSI). However, this requirement results in an increased overhead, especially in time-varying channels, which reduces the resources that can be used for data communication. In this paper, we consider the uplink between a single-antenna user and a multi-antenna BS and present a novel RS-empowered Orthogonal Frequency Division Multiplexing (OFDM) communication system based on the differential phase shift keying, which is suitable for high noise and/or mobility scenarios. As a benchmark, analytical expressions for the Signal-to-Interference and Noise Ratio (SINR) of the proposed system are presented. Our extensive simulation results verify the accuracy of the presented analysis and showcase the performance and superiority of the proposed system over coherent demodulation.

Reconfigurable Intelligent Surfaces (RISs) are an emerging technology in the evolution towards the Sixth Generation (6G) of mobile communications. They are capable of enhancing the overall system performance and extending the coverage of the existing cells. They are built by a large amount of low-cost meta-elements that can be configured by tuning their phase shifts, and hence, the channel response can be constructively combined and forwarded to some specific direction. Many algorithms have been proposed to obtain the optimum phase shifts, generally assuming a single-carrier system and/or a medium-size RIS to constrain the complexity of the optimization process. In this work, we propose a flexible and scalable unsupervised learning model, capable of obtaining the best phase shifts for any scenario. Our proposal is able to handle multi-carrier waveforms and very large-size RIS, considering both continuous and discrete phase shifts. Besides, we also propose the use of clustering to reduce further the complexity while maintaining the performance. A comparison in terms of achievable rate and time execution is provided in order to show the superiority of our proposal against the existing solutions.

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.

A rigorous analysis of the effect of spatial correlation for non-coherent (NC) massive multiple-input-multiple-output (MIMO) in Rician channels is important to determine its applicability in these scenarios. We conduct such analysis for a single base station (BS) and a more general case of several BSs, all of them showing correlation among their own antennas but with uncorrelated channels with respect to each other. We first perform an analysis of the distribution of the received symbols, then propose some approximations to give a closed form expression of the symbol error probability (SER) and the signal-to-interference-and-noise-ratio (SINR) as performance measures. Finally, we extract some conclusions from this analysis to show how the combined use of several BSs and larger Rician components can be beneficial in this scenario. Some numerical results are added to confirm the accuracy of the analysis.

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.

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.

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.

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.

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.

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.