Emerging technologies like Fluid Antenna Systems (FAS) are important ingredients toward new generation communications. In particular, we focus on systems based on the reconfigurability capabilities of liquid antennas, which are a subset of FAS that use a liquid as their main conductor. Despite recent pertinent advances in the field, the reconfiguration speed was not directly addressed in the literature, as it is assumed to be very high in most works. However, it is a crucial parameter that defines the system’s capabilities and performance bounds. In addition, a few approaches to spatial correlation modeling are presented here that are also needed for a holistic performance evaluation. Hence, a numerical methodology is proposed to realistically model both parameters. Performance metrics are also addressed, which aid in identifying and comprehending the system’s strengths and weaknesses. The importance of these models and metrics is showcased by reconfiguring the FAS, proposing several algorithms and illustrating their features. As a result, we show that it is possible to obtain a realistic performance evaluation for FAS and improve currently available models and performance to further progress on this topic.

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.

This paper introduces a novel Reference Signal and a channel estimation and equalization technique for Zero-Padded waveforms, like ZP-OFDM and the recently proposed FM-OFDM, under doubly-dispersive channels with Doppler and phase noise. We describe a two-stage pilot structure aimed to separately capture the long-term and short-term channel variations and a piecewise estimation and equalization technique, based on approximation of the time-varying channel impulse response by a set of time-invariant channel responses, which are independently equalized and further combined to compensate the channel’s dispersion. Design criteria for the proposed Reference Signal are also given. Numerical results under high phase noise show that piecewise-equalized ZP-OFDM can outperform MMSE-equalized CP-OFDM with CPE compensation, thus avoiding the need of an additional Reference Signal for phase noise mitigation. Results under high mobility demonstrate the superiority of piecewise-equalized FM-OFDM and ZP-OFDM waveforms over MMSE-equalized OTFS and CP-OFDM, outperforming also the highly complex DFE-equalized OTFS for certain modulation orders, without the need to estimate any Doppler components. The degradation incurred by the proposed realistic piecewise estimation technique with respect to ideal estimation depends on the richness of the channel’s multipath profile rather than its Doppler spread.

This paper investigates a reconfigurable intelligent surface (RIS)-aided wideband massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with low-resolution analog-to-digital converters (ADCs). Frequency-selective Rician fading channels are considered, and the OFDM data transmission process is presented in time domain. This paper derives the closed-form approximate expression of the uplink achievable rate, based on which the asymptotic system performance is analyzed when the number of the antennas at the base station and the number of reflecting elements at the RIS grow to infinity. Besides, the power scaling laws of the considered system are revealed to provide energy-saving insights. Furthermore, this paper proposes a gradient ascent-based algorithm to design the phase shifts of the RIS for maximizing the minimum user rate. Finally, numerical results are presented to verify the correctness of analytical conclusions and draw insights.

Visible light communication (VLC) is a technology that complements radio frequency (RF) to fulfill the ever-increasing demand for wireless data traffic. The ubiquity of light-emitting diodes (LEDs), exploited as transmitters, increases the VLC market penetration and positions it as one of the most promising technologies to alleviate the spectrum scarcity of RF. However, VLC deployment is hindered by blockage causing connectivity outages in the presence of obstacles. Recently, optical reconfigurable intelligent surfaces (ORISs) have been considered to mitigate this problem. While prior works exploit ORISs for data or secrecy rate maximization, this paper studies the optimal placement of mirrors and ORISs, and the LED power allocation, for jointly minimizing the outage probability while keeping the lighting standards. We describe an optimal outage minimization framework called JointMinOut and present solvable heuristics. We provide extensive numerical results and show that the use of ORISs may reduce the outage probability by up to 67% with respect to a no-mirror scenario and provide a gain of hundreds of kbit/J in optical energy efficiency with respect to the presented benchmark.

Visible light communication (VLC) has emerged as an alternative to radio-frequency (RF) systems and promising technology for high-speed wireless communications. In this context, spatial Multiple-Input Multiple-Output (MIMO) techniques have been widely investigated to enhance the performance of VLC systems by exploiting the spatial domain for transmitting multiple data streams simultaneously. The conventional focus has primarily been on optimizing transmitter configurations, overlooking the significance of receiver design. In this paper, we shed light on the necessity of incorporating angular diversity receivers in spatial MIMO VLC systems to mitigate channel impairments and improve the overall performance. Through extensive simulations and analysis, we demonstrate the benefits of angular diversity receivers in terms of enhanced signal reception, increased data rates, and improved link robustness in various indoor scenarios. Our findings underscore the importance of considering both transmitter and receiver aspects for the advancement of spatial MIMO VLC technology.

Visible light communication (VLC) complements radio frequency in indoor environments with large wireless data traffic. However, VLC is hindered by dramatic path losses when an opaque object is interposed between the transmitter and the receiver. Prior works propose the use of plane mirrors as optical reconfigurable intelligent surfaces (ORISs) to enhance communications through non-line-of-sight links. Plane mirrors rely on their orientation to forward the light to the target user location, which is challenging to implement in practice. This paper studies the potential of curved mirrors as static reflective surfaces to provide a broadening specular reflection that increases the signal coverage in mirror-assisted VLC scenarios. We study the behavior of paraboloid and semi-spherical mirrors and derive the irradiance equations. We provide extensive numerical and analytical results and show that curved mirrors, when developed with proper dimensions, may reduce the shadowing probability to zero, while static plane mirrors of the same size have shadowing probabilities larger than 65%. Furthermore, the signal-to-noise ratio offered by curved mirrors may suffice to provide connectivity to users deployed in the room even when a line-of-sight link blockage occurs.

Spectrum sensing plays a very important role in Cognitive Radio-based Internet of Things (CR-IoT) networks for utilization of the licensed spectrum accurately. However, the performance of the conventional Energy Detection (ED) method is compromised in a noise-uncertain environment owing to interference constraints, i.e. the CR-IoT user interference to the licensed Primary User (PU) on the same licensed band. To overcome this drawback, we proposed an energy efficient Cooperative Spectrum Sensing (CSS) for a CR-IoT network with interference constraints using a novel ED method. In this method, each CR-IoT user is capable of spectrum sensing using both the local decision and the weight factor based on a sequential approach; we calculate the weight factor against each CR-IoT user based on the Kullback Leibler Divergence award score. After the local decision and the weight factor are obtained, each CR-IoT user transmits both the local decisions and the weight factor to a Fusion Center (FC), which makes a final decision about the PU activities based on the hard fusion rule. The simulation results demonstrate that the proposed ED method obtains an improved detection performance, an enhanced sum rate, better spectral efficiency and energy efficiency, and a lower global error probability when compared to other conventional ED methods under time varying environments.

Spectrum sensing is a vital phase in the cognitive radio cycle for the fifth generation. However, it is vulnerable when the malicious users send their falsification information to the fusion center (FC). Due to the fact that the secure spectrum sensing is required to avoid collision between the primary users and secondary users. In this paper, we propose a secure spectrum sensing in cognitive radio-enabled Internet of things (CR-IoT) networks using a hybrid deep learning (DL)-vision transformer (ViT)-gated recurrent unit (GRU)-based mod-ulation index with constellation diagrams. It enhances security by separating unauthorized CR-IoT users and authorized CR-IoT users from CR-IoT networks. Avoiding the unauthorized CR-IoT users degrades the detection gain performance. According to simulation results, the proposed hybrid DL-ViT-GRU model performs better detection accuracy in terms of security.

This paper contributes by providing a comprehensive set of block error rate (BLER) vs. signal-to-noise ratio (SNR) curves under additive white Gaussian noise (AWGN) channel conditions for 5G new radio (NR) modulation and coding schemes (MCS) belonging to the 3GPP 5G NR TS 38.214 standard, with low-density parity check (LDPC) coded scenario according to TS 38.212. To enhance practical relevance in the context of O-RAN networks, this paper also introduces the effect of optimum quantization and compares the results without quantization, showing that despite system degradation, the performance remains very close to the unquantized case. By providing this comprehensive dataset, the paper offers valuable insights to support the selection of the most appropriate MCS depending on the required BLER-SNR scenario, serving as a guide in the design of 5G communication systems, for the scheduler, and as lookup tables for the physical layer (PHY) abstraction in link-level simulators (LLS).

The increasing demand for bandwidth has led fifth generation (5G) mobile communication systems to adopt the use of millimeter waves (mmWaves), to enable higher data rates. However, operating at such high frequencies poses technological challenges, one of the most prominent being the phenomenon known as phase noise (PN), which degrades the system, especially when combined with the orthogonal frequency-division multiplexing (OFDM) waveform. Traditionally, this effect is corrected by using exclusively dedicated pilots for PN tracking, which severely degrade the data rate. This paper presents pilotless machine learning (ML)-based methods for estimating and compensating PN with the goal of eliminating the need for pilots, leading to a substantial increase of the data rates. In addition, this paper demonstrates the feasibility of these solutions for practical mmWaves deployments through tests with real measurements in an experimental setup using an mmWave 5G-developed platform.

In recent years, advances in immersive multimedia technologies, such as extended reality (XR) technologies, have led to more realistic and user-friendly devices. However, these devices are often bulky and uncomfortable, still requiring tether connectivity for demanding applications. The deployment of the fifth generation of telecommunications technologies (5G) has set the basis for XR offloading solutions with the goal of enabling lighter and fully wearable XR devices. In this paper, we present a traffic dataset for two demanding XR offloading scenarios that substantially extend those available in the current state of the art, captured using a fully developed end-to-end XR offloading solution. We also propose a set of accurate traffic models for the proposed scenarios based on the captured data, accompanied by a simple and consistent method to generate synthetic data from the fitted models. Finally, using an open-source 5G radio access network (RAN) emulator, we validate the models both at the application and resource allocation layers. Overall, this work aims to provide a valuable contribution to the field with data and tools for designing, testing, improving, and extending XR offloading solutions in academia and industry.

In this paper, to tackle the blockage issue in massive multiple-input-multiple-output (mMIMO) systems, a reconfigurable intelligent surface (RIS) is seamlessly deployed to support devices with ultra-reliable and low-latency communications (URLLC). The transmission power of the base station and the phase shifts of the RIS are jointly devised to maximize the weighted sum rate while considering the spatially correlation and channel estimation errors. Firstly, the relationship between the channel estimation error and spatially correlated RIS’s elements is revealed by using the linear minimum mean square error. Secondly, based on the maximum-ratio transmission precoding, a tight lower bound of the rate under short packet transmission is derived. Finally, the NP-hard problem is decomposed into two optimization problems, where the transmission power is obtained by geometric programming and phase shifts are designed by using gradient ascent method. Besides, we have rigorously proved that the proposed algorithm can rapidly converge to a sub-optimal solution with low complexity. Simulation results confirm the tightness between the analytic results and Monte Carlo simulations. Furthermore, the two-timescale scheme provides a practical solution for the short packet transmission.

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.

Visible light communication (VLC) is a growing technology that can complement radio frequency to fulfill the increasing demand for wireless data services. VLC exploits the already deployed illumination infrastructure based on light-emitting diodes to communicate data. While mirrors have been traditionally used for interior decoration, among other applications, to what extent can they be deployed to improve VLC performance? In this paper, we propose optimizing the placement of mirrors to minimize the outage area, a common problem in VLC when line-of-sight link blockage occurs. We compare this optimal performance with a single-rectangular mirror array, a common mirror shape that is found indoors. We also study the most helpful mirror placement under different conditions. We show that our outage minimization algorithm, MinOut, easily provides threefold outage reductions. Besides, we demonstrate that a single-rectangular mirror array with orientation mobility can provide similar or even better performance than an optimal distributed mirror placement without mobility.

This work provides a performance assessment of hybrid relay-connected multi re-configurable intelligent surfaces (M - RIS)-empowered systems for coverage extension. In particular, novel end-to-end SNR expressions for probability density function$(p_{\gamma_{d,N}})$, cumulative distribution function$(F_{\gamma_{d,N}})$, outage probability$(P_{\gamma_{d,N}})$, average bit error rate$(P_{e,N})$and ergodic channel capacity$(C_{d,N})$for the considered hybrid relay connected M-RIS empowered systems over independent Rayleigh fading channels are derived and numerically evaluated. Moreover, this work provides a comparative performance analysis between hybrid triple (T)-RIS, hybrid double (D)-RIS and single (S)-RIS empowered systems subjected to Rayleigh fading conditions in terms of the considered measures. It has been observed that the M-RIS empowered system equipped with large number of RIS elements (L) can not only broaden coverage but can also outperform the S-RIS empowered system.

This paper introduces a novel waveform for wireless communication, denoted as Frequency-Modulated Orthogonal Frequency-Division Multiplexing (FM-OFDM). By frequency-modulating an OFDM signal and further defining a suitable cutoff subcarrier, the resulting constant-envelope waveform (ensuring a low Peak to Average Power Ratio) exhibits strong robustness not only to Doppler, but also to phase noise and carrier frequency offsets. These impairments introduce an additive error term at the information-bearing subcarriers that is mostly concentrated at the lowest part of the spectrum. No inter-carrier interference is thus present, and impairments can be easily overcome by mapping the information above a cutoff subcarrier. Theoretical expressions and numerical results prove the superiority of FM-OFDM over the state of the art, particularly in high-speed Rayleigh channels and/or high phase noise.

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.

Performance analysis and channel modelling of unmanned-aerial-vehicle (UAV) communication links are an im-portant task for a reliable deployment of 5G and future 6G UAV assisted wireless communication networks (WCNs). UAV-to-ground (U-G) type of communications in densely populated areas due to dynamic and highly varying propagation conditions are usually characterized by composite fading channels. This paper considers the extension of the recently proposed and experimentally verified double-scattered double-shadowed (ds-ds) composite fading model for U-G communications. We model the ds-ds fading channel as a product of double generalized gamma (d-GG) and double inverse gamma (d-IG) random variables (RV s) and provide novel SNR expressions for the probability density function (pdf) and cumulative distribution function (cdf) expressed in terms of MeijerG and BesselK functions. Based on the derived pdf and cdf statistics, we assess performance metrics (P-M) of U-G communications in terms of outage probability, average bit error rate and ergodic channel capacity. Numerical results for the observed P-M are presented and analyzed for various sets of ds-ds fading propagation parameters.

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.

Visible light communication (VLC) is considered a promising technology for providing high data rates in indoor environments. In this sense, each optical access point (AP) in a VLC network can be managed as a small cell usually referred to as attocell. Therefore, the received signal is subject to both multi-user interference (MUI) and inter-cell interference (ICI). In this work, we propose a user centric (UC) cell formation approach jointly with the use of blind interference alignment (BIA) in order to manage the interference. We formulate an optimization problem based on maximizing the sum utility of users rates for the sake of jointly finding the optimal cell formation and minimizing the limitations of BIA, i.e., the noise enhancement and the required coherence time given by the mobility of the users. This problem can be solved through exhaustive research, which involves an unpractical complexity. After that, we decouple the main problem into two sub-problems that may be solved separately. The simulation results show that the proposed schemes are more suitable for VLC networks than the considered benchmark schemes.

The arrival of the fifth generation (5G) of mobile communications is boosting vehicular communications, an important use case addressed in the recent years. LTE introduced a sidelink radio interface through which user equipment would communicate directly with no necessary dependence on the network, named PC5. 5G has defined its own sidelink interface, NR-Sidelink, envisaged to improve PC5. This paper analyses the use of Demodulation Reference Signals (DMRS) to estimate the channel in sidelink communications. Improving several mappings proposed by the standards, the main contribution proposed in this paper is a new DMRS mapping with a better performance. The proposed Unequal Pilot Spacing (UPS) mapping can enhance the standard with a satisfactory trade-off between performance and overhead.

Heterogenous networks are mainly limited by interference. Nowadays, the advances in reconfigurable antennas allow us to implement blind interference alignment (BIA) schemes, which avoid the need for channel state information at the transmitter (CSIT) while providing an increasing multiplexing gain, i.e., the achievable DoF, as the number of users increases. In this work, we propose a downlink transmission scheme based on BIA for managing the inter-tier interference in$K$-tier networks, referred to as tier BIA (tBIA). The tBIA scheme can be implemented considering that each tier employs any BIA scheme for managing the intracell and intercell interference. In this sense, considering proper BIA schemes applied to each tier, tBIA fully cancels all the sources of interference. After that, the DoF outer-bound for$K$-tier networks without CSIT is derived. It is shown that tBIA reaches this outer-bound. Furthermore, it is demonstrated that fully managing the inter-tier interference provides larger DoF in the whole network than turning off any tier with the aim of improving the achievable DoF in the remaining tiers. Simulation results show that the proposed tBIA scheme provides greater DoF and improves the user rates in comparison with other schemes without CSIT in multi-tier networks.

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.

The application of non-orthogonal multiple access (NOMA) to downlink multi-user multiple-input single-output systems involves the design of a beamforming strategy in which the spatial dimension provided by each beam is shared among several users performing NOMA. This approach requires the management of both inter-cluster and intra-cluster interference. Moreover, the beamforming design is subject to instantaneous knowledge of the channel state information at the transmitter (CSIT). We propose a novel transmission scheme that combines blind interference alignment and NOMA. The proposed scheme fully cancels the inter-cluster interference for all users without the need for instantaneous CSIT, which is limited to the knowledge of the large scale effects of the channel in order to implement NOMA within each cluster. Considering user pairing, i.e., each cluster is composed of two users, we derive a method for determining the NOMA power coefficients that maximize the sum-rate, the user fairness or satisfy first the rate of a specific user by simply solving a polynomial function. Furthermore, we propose an alternative methodology based on some approximations in order to provide sub-optimal closed-form expressions of these NOMA power coefficients. Simulation results show that the proposed scheme outperforms conventional MISO-NOMA taking into consideration the costs of providing CSIT.

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.

We characterize the degrees of freedom (DoF) of the two-tier heterogeneous networks without channel state information at the transmitters or cooperation among transmitters. We consider conventional transmitters while the users are equipped with a multimode receiver. In contrast to previous works focused on two-tier networks, the derived DoF consider the management of the intracell, the intercell, and intertier interference. The derived bounds define the DoF region for any two-tier network. Furthermore, these bounds are achievable by combining blind interference alignment schemes properly.

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.

Visible light communications (VLC) have been pro- posed as a means of moving part of the indoor traffic to the optical spectrum. The deployment of LED lights for data transmission forming attocells in the cellular networks known as Light-Fidelity (LiFi) interacts with other radiofrequency (RF) based networks such as WiFi or femtocells. Since LED lights illuminate a small confined area and interfere with other LED lights, the hybrid network composed of the LiFi and RF systems can be employed for resource management allocating each user to a specific network. In this work, we consider the use of a novel inference management scheme for LiFi known as Blind Interference Alignment (BIA) that avoids both the multi-user and the intercell interference. However, BIA schemes are limited by noise increase due to interference subtraction and the channel coherence block requirement, which increase with the number of user served by the LiFi network. It is shown that the hybrid LiFi/RF network allow to relax the requirements for BIA implementation and increase the sum- rate of the whole network.

The use of light-emitting diodes (LEDs) for ambient illumination leads to visible light communications (VLC) as a promising technology for providing both constant lighting and high-speed wireless services in indoor environments. Since multiple LED sources can be transmitted to several users, this scenario naturally forms a multiple-user multiple-input single-output system. In this sense, transmit precoding (TPC) schemes based on channel state information at the transmitter (CSIT) originally devised for radio-frequency (RF) systems have been proposed for their implementation in VLC. However, beyond providing CSIT or the need for cooperation among transmitters, which also result challenging in RF systems, there are several constraints such as the non-negativity of the transmitted signal or providing constant illumination that hamper the performance of TPC schemes in VLC. Considering these constraints, this paper explores the use of blind interference alignment (BIA) for achieving multiplexing gain without CSIT or cooperation among LED lights. To do that, we devise the concept of reconfigurable photodetector that allows switching among distinct and linearly independent channel responses. Simulation results show that the use of BIA in VLC systems schemes based on the proposed reconfigurable photodetector results suitable for VLC systems.

Carrier aggregation increases the throughput of LTE mobile networks by aggregating bandwidth at different frequencies. The theoretical effectiveness of carrier aggregation has been widely studied in the literature and operators claim it substantially increases the network data rate. However, to the best of our knowledge no practical evaluation of the performance of carrier aggregation has been performed using real traffic data. We perform a thorough measurement-based study to assess how carrier aggregation improves the service offered in selected locations in Madrid, Spain. Although the best results for data rate boost are in line with the operator claims, we find that resource usage in aggregated bands is frequently suboptimal, and higher data rates could be achieved by simply overloading a single band. On the other hand, the quality of service achieved by users effectively exploiting carrier aggregation could not be achieved without it.

In this paper, we analyze the effect of time-varying channels on the performance of a non-coherent massive single-input multiple-output (SIMO) uplink system based on M-ary Differential Phase Shift Keying (M-DPSK), when amalgamated with bit-interleaved coded modulation relying on iterative decoding (BICM-ID). Additionally, we study the number of receive antennas (R) required in hostile time-varying channels for attaining a similar performance to that achieved for stationary channels. Furthermore, we analyze the maximum achievable rate (MAR) in conjunction with the specific modulation and coding schemes considered. The analysis is based on extrinsic information transfer (EXIT) charts parametrized by R, which varies with the signal to interference-plus-noise ratio (SINR). Our numerical results show that the system is robust to the effects of the channel's temporal correlation and that the simulation-based MAR closely matches the semi-analytical achievable rate obtained using EXIT charts. Hence,our system can be applied to scenarios associated with the short coherence time of high-speed railway systems, for example.

The use of current narrowband Private Mobile Radio (PMR) systems, such as Terrestrial Trunked Radio (TETRA) still has significant shortcomings for public safety networks. In disaster situations, for first responder emergency services to communicate more effectively, the exchange of multimedia information (e.g. high-resolution images) could really help. Due to this fact, LTE technology is postulated as the choice for public safety broadband communication systems. In this paper, we examine a proposal based on two-hop links that seeks to reach locations with low or null coverage and to achieve a physical layer improvement. Such a solution is carried out by combining some LTE features provided by the Third Generation Partnership Project (3GPP) with the use of a wearable massive MIMO solution formed by a large textile array directly implemented at the end user.

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.

Massive MIMO has been proposed as a means of achieving huge spectral efficiency in cellular networks. However, its implementation is usually based on linear precoding schemes using Channel State Information (CSI). For this reason, the use of the Time Division Duplex (TDD) mode is typically assumed since it removes the dependence on the number of antennas at the transmitter to acquire CSI. Unfortunately, most of the cellular network operate in the Frequency Division Duplex (FDD) mode in which the acquisition of CSI depends proportionally to the number of transmit antennas. For this reason, the implementation of Massive MIMO is handicapped to few transmit antennas for the current cellular networks. In this paper we study the use of reconfigurable antennas that can switch among a set of preset modes, i.e., radiation patterns, through Blind Interference Alignment schemes. We show that it is a solution to exploit a very large number of antennas at the transmit side, overcoming the bottleneck that today constitutes the acquisition of CSI in Massive MIMO systems operating in FDD mode.

Rescue tasks in coal mines are fundamental but often suppose the loss of rescuers lives, as currently they are carried out only by humans. TeleRescuer project expects to make this activity safer by developing a robot to be driven by rescuers from a safe area. It offers virtual teleportation providing to the operator an environment where he can interact with the reality perceived by the robot. In this paper, the design of the communication, vision and sensory systems are presented, giving an overview of all the elements that are included in the robot. The adaptation of these electronics to the hazardous environment is also explained. A prototype of an ad-hoc wireless network and results in terms of the transmission characteristics are shown.

A practical Blind Interference Alignment scheme is devised for the broadcast channel where the users are equipped with reconfigurable antennas. The proposed scheme does not require any channel state information at the transmitter other than the signal-to-noise ratio and coherence time. By employing Blind Interference Alignment to transmit to sets of users in an orthogonal fashion, the proposed scheme aims at maximizing the sum-rate at a finite signal-to-noise ratio regime and allows to handle the supersymbol length according to the coherence time limitation. Through computer simulations, it is shown that the proposed scheme improves the sum-rate of the system considerably in comparison with the standard Blind Interference Alignment in practical scenarios.

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.

A non-coherent detection assisted Differential Phase Shift Keying aided large-scale MIMO system is designed in a wireless uplink where multiple single-antenna users are transmitting to the base station's receiver equipped with a very large number of receive antennas. We show that the signal to interference plus noise ratio (SINR) scales with the number of receive antennas, which confirms the same scaling law found in coherent systems. We propose a range of constellation designs that allow us to separate the users' signals at the receiver by relying only on the knowledge of the average received power per user. We analyse the error probability and provide insights into the beneficial selection of the constellation parameters. Finally, we provide some numerical results showing that our proposals require a lower number of receive antennas to achieve a given error probability than other non-coherent benchmark schemes available in the literature, while they are not far from an equivalent coherent system relying on realistic channel estimation settings.

An experimental evaluation of Blind Interference Alignment (BIA) over a hardware platform is presented in this work. In contrast to other transmission techniques such as Linear Zero Forcing Beamforming (LZFB) or Interference Alignment (IA), BIA achieves a growth in Degrees of Freedom (DoF) without channel state information at the transmitter (CSIT). A real implementation based on Orthogonal Frequency Division Multiplexing (OFDM) and LTE parameters is implement on a testbed made up of a transmitter equipped with two antennas and two users equipped with a reconfigurable antenna each. Furthermore, a full CSIT technique such as LZFB is also implemented for comparison purposes. First, the theoretic achievable rates are obtained for both techniques. After that, the bit error rate of both schemes is evaluated regarding the achieved sum-thorughput.

A cognitive Blind Interference Alignment scheme is devised for use in macro-femto cellular networks. The proposed scheme does not require any channel state information at the transmitter or data sharing among the Macro Base Station and the Femto Access Points. It achieves transmission to femto cell users without affecting the rates of the Macro users. This is achieved by appropriately combining the supersymbols of the Macro Base Stations and the Femto Access Points. It is shown that in some scenarios the use of this scheme results to considerable rates for Femto users.

A cooperative blind interference alignment (BIA) strategy is considered for the downlink of cellular systems. The aim is to reduce intercell interference in order to protect users, especially at the cell edge. The strategy consists of appropriately splitting the available bandwidth and is shown to be well-suited to scenarios where the number of cell-edge users is considerable. For a system comprising two cells each with a base station of Ntantennas, it is shown that, compared to a previous augmented code approach where transmission to all users occurs in the same frequency band, the proposed strategy leads to better rates over a wide range of signal-to-noise ratios when the number of cell-edge users in both cells exceeds 2Nt-1.

Radio over Fiber (RoF) distribution aided co-operation of Remote Access Points (RAPs) is proposed for jointly transmitting data to the users in the downlink (DL) of a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. Joint transmission is performed with the aid of Block Diagonalization (BD), where the transmitted signal is pre-distorted in order to overcome the non-linearity imposed by the optical modulator. We demonstrate that with adequate design, the users can obtain high data rates with very small degradation introduced by the RoF transmission. Quantitatively, when M=7 RAPs, each equipped with t=2 transmit antennas (TAs) each, cooperate to serve N=7 simultaneous users, also equipped with r=2 receive antennas (RAs), the SNR degradation is kept below 0.1 dB compared to a system assuming a perfect RoF channel. On the other hand, the SNR performance degradation is around 1.2 dB, when the number of antennas at the transmitters and the receivers is increased to t=r=8.

In a multicast video streaming service over a cellular network, the same content is sent to a mass audience using a common channel. However, users belonging to the same multicast channel perceive different characteristics of the radio channel. Moreover, in wireless environments, the radio interface introduces an important level of interference and noise, resulting in a high rate of transmission errors. Therefore, a protection of the information is needed at each receiver using Forward Error Correction (FEC) schemes, which allow the recovery of the lost packets sending redundancy together with the payload. FEC solutions can be used in combination with other techniques to overcome the existing limitations of the mobile network, in particular, the use of a single-frequency network to prevent the effect of destructive signal interference. This paper analyzes the performance of a video streaming service comparing different FEC schemes, Raptor and RaptorQ codes, where some system parameters can be tuned in a single-frecuency network.

We consider the downlink coordinated beamforming problem in a cellular network in which the base stations (BSs) are equipped with multiple antennas and each user is equipped with a single antenna. The BSs cooperate in sharing their local interference information, and they aim to maximize the sum-rate of the users in the network. A decentralized interference pricing beamforming (IPBF) algorithm is proposed to identify the coordinated beamformer, where a BS is penalized according to the interference it creates to its peers. We show that the decentralized pricing mechanism converges to an interference equilibrium, which is a KKT point of the sum-rate maximization problem. The proofs rely on the identification of rank-1 solutions of each BSs' interference-penalized rate maximization problem. Numerical results show that the proposed iterative mechanism reduces significantly the exchanged information with respect to other state-of-the-art beamforming algorithms with very little sum-rate loss. The version of the algorithm that limits the coordination to a cluster of base stations (IPBF-L) is shown to have very small sum-rate loss with respect to the full coordinated algorithm with much less backhaul information exchange.

We present partial coordination strategies in a clustered cellular environment, evaluating the achievable rate in the downlink transmission. Block Diagonalization is employed for the coordinated users within the cluster to remove interference, while the interference from non-coordinated users remains. The achievable rate is evaluated resorting to an analytical expression conditioned on the position of the users in the cluster. A partial coordination approach is proposed to reduce the coordination complexity and overhead, where users close to the base station are not coordinated. Two approaches are considered, namely the non-coordinated users can be grouped and assigned separated resources from the coordinated ones, or they can be mixed.

We focus on the mean achievable rate per user of the coordinated base station downlink transmission in a clustered cellular environment, with transmit power constraints at the base stations. Block Diagonalization is employed within the cluster to remove interference among users while the interference from other clusters remains. The average achievable rate per user is evaluated considering the effects of the propagation channel and the interference and a theoretical framework is presented to provide its analytical expression, validated by simulation results with different power allocation schemes. As an application, the number of cells of the cluster that maximizes the mean achievable rate per user is investigated. It can be seen that in most of the cases a reduced cluster size, close to seven cells, guarantees a rate very close to the maximum achievable.

Bit and power loading schemes for a single-user multiple-input multiple-output channel using a minimum mean-square error receiver are proposed. Such schemes are derived without the benefit of instantaneous channel state information (CSI) at the transmitter, on the basis of only statistical CSI. They exploit the relationships between the average bit error probability at the receiver and the power allocation at the transmitter, in the context of spatially correlated Rayleigh fading. The performance of the proposed schemes is then benchmarked with respect to both non-adaptive transmission and to an adaptive counterpart with a zero-forcing receiver.

In this letter the discrete rate maximization problem is investigated for FBMC/OQAM. The analysis reveals that if there is crosstalk certain bit allocations violate the power constraints. Aiming at ensuring the feasibility along with alleviating the complexity we have devised a novel iterative algorithm, which always converges. Simulation-based results show that the proposed algorithm performs close to the upper bound for high-coherence bandwidth channels. Under highly frequency selective channels the existing algorithms are not able to guarantee the target SER whereas our approach guarantees the QoS.

A relay station (RS)-based cellular system deployment is considered, where multiple base stations (BS) cooperate in the BS-RS in-band transmission for the downlink. With the joint optimization of the resources allocated to the wireless backhaul and to the RS-MS access, it is possible to exploit the benefits of networked-MIMO along with combating the pathloss and shadowing effects, and thus obtain significantly enhanced spectral efficiency and coverage homogeneity. The problem is shown to be convex under conventional QoS objective functions. Suboptimal low complexity solutions are also proposed and evaluated.

In a Coordinated Base Station Transmission scenario for the downlink, we propose a precoding scheme based on a MMSE criterion to manage the inter-user interference. In order to allocate the transmitted power to each user's signal, we set up an iterative procedure based on a modified waterfllling distribution, which approaches the optimal performance with a viable complexity with respect to the numerical optimization. A further simplification may be introduced, giving a simple iterative waterfilling scheme, at the expense of some performance loss. The performance is illustrated obtaining the achievable rates for different antenna configurations and different kinds of power constraints. A comparison with a Block-Diagonalization approach shows the advantage of MMSE, in particular at low SNR.

In this work we consider the interference between femtocells in a High Speed Downlink Packet Access (HSDPA) system. When no specific interference management technique is applied the performance,measured in terms of HSDPA throughput, is quite poor. A Zero Forcing Coordinated Base Station Transmission scheme is proposed as a solution to cancel interference. The simulations in representative scenarios show that the desired throughputs can be achieved when all femtocells exploit common knowledge of channel state and user data.

This paper addresses the problem of resource allocation in a multiple access channel where several mobile terminals (MT's) are transmitting simultaneously to a single receiving base station, all of them with multiple antennas and exploiting beamforming. A multi-carrier modulation is assumed, either orthogonal frequency division multiplexing (OFDM) or filter bank multi-carrier (FBMC). The main advantage of FBMC is that the spectrum of the sub-channels is much more concentrated than for OFDM. This property is explicitly exploited in this paper in order to evaluate an asynchronous network where the transmissions from different MT's are not aligned in time. This implies that a frequency guard between groups of carriers assigned to different users has to be included, being larger for OFDM than for FBMC. The improvement in performance due to this fact is evaluated by means of the rate that can be achieved by dynamically allocating carriers to users and by calculating the power and bit loading to be applied.

In this paper, a novel scheme for reducing the envelope fluctuations in multi-carrier signals applying Adaptive Neural Fuzzy Inference Systems (ANFIS) is proposed and analyzed. Once trained with signals with very low envelope fluctuations, such as those obtained by the Active Constellation Expansion - Approximate Gradient Project (ACE-AGP) algorithm, ANFIS approximately reaches a similar reduction as with ACE-AGP for multi-carrier signals without the complexity and the large convergence time of conventional ACE-AGP. We show that our approach is less complex than other previous schemes and with better performance.

In this letter, the multiuser bit and power allocation problem for an orthogonal frequency division multiplexing (OFDM)/offset-quadrature amplitude modulation (OQAM) system is investigated. The signal-to-interference-plus-noise ratio (SINR) and required power expressions for the formulation of the problem in an OFDM/OQAM system are developed. Next, a suboptimal algorithm based on this formulation is proposed.

The phase noise effect in multiple-input-multiple-output systems employing orthogonal frequency division multiplexing is considered in a realistic scenario where the estimated channel matrix is affected by an error. The analytical SINR degradation due to phase noise and channel estimation is obtained for linear receivers (ZF and MMSE).

For single-user MIMO communication with uncoded and coded QAM signals, we propose bit and power loading schemes that rely only on channel distribution information at the transmitter. To that end, we develop the relationship between the average bit error probability at the output of a ZF linear receiver and the bit rates and powers allocated at the transmitter. This relationship, and the fact that a ZF receiver decouples the MIMO parallel channels, allow leveraging bit loading algorithms already existing in the literature. We solve dual bit rate maximization and power minimization problems and present performance results that illustrate the gains of the proposed scheme with respect to a non-optimized transmission.

In this contribution we analyze the performance of several transmission strategies in a MIMO-OFDM system deployed in a wireless metropolitan area network. With this aim, a measurement campaign has statistically characterized a typical outdoor-indoor scenario for wireless metropolitan area networks. The performance is measured in terms of spectral efficiency under several channel knowledge scenarios at the transmitter and power allocation matrices that lead to different transmission strategies. Also two alternatives (averaging in the time or frequency domains) are explored in order to provide the transmitter with the information needed to implement the transmission strategy when it is only possible to get information about the channel statistics.

In this work the effect of phase noise in multiple-input-multiple-output systems employing orthogonal frequency division multiplexing is considered in a realistic scenario where channel estimation is not perfect, so that the channel matrix used at the receiver to perform demodulation is affected by an estimation error. In particular, it is shown that the actual degradation depends on the scheme employed in the receiver. The zero-forcing scheme, although giving a slightly worse performance for the perfectly known channel, proves to be more robust to the effects of channel estimation errors in the presence of phase noise.

A new$[47,15,16]$linear binary block code and its weight spectrum is presented. The code is better than the previously known$[47,15,15]$code and it reaches the upper bound on code distance for the codeword length$47$and dimension$15$.

LS and MMSE phase noise estimation and correction schemes are proposed for orthogonal frequency division multiplexing (OFDM). Their performance is characterized in channels impaired by AWGN and multipath effects. The required separation between pilot symbols in the OFDM frame is analyzed leading to the conclusion that the proposed schemes are feasible with a very small efficiency loss caused by pilot insertion.

Adaptive OFDM has the potential of providing bandwidth-efficient communications in hostile propagation environments. Currently, bit loading algorithms use M-ary quadrature amplitude modulation of the OFDM sub-carriers, where the number of bits per symbol modulating each of them is obtained in order to maximize the performance. SNR gap approximation for M-QAM signaling makes the algorithms simpler to implement. However, in some circumstances it may be preferable to use. M-ary phase shift keying. In this letter an approximation is derived for M-PSK similar to the SNR gap of M-QAM so that bit loading algorithms can be extended to this type of modulation. In addition, the performance obtained when using M-PSK is compared to that of M-QAM in a practical situation.

We present a new approach to nonparametric spectral estimation on the basis of the support vector method (SVM). A reweighted least squares error formulation avoids the computational limitations of quadratic programming. The application to a synthetic example and to a digital communication problem shows the robustness of the SVM spectral analysis algorithm.

Turbo coding performance is studied for an UMTS scenario. Several mobile channel models are implemented and the effect of the correlation fading on the coding performance is studied.

Bit loading algorithms use M-ary quadrature amplitude modulation (M-QAM) of the OFDM sub-carriers, where the number of bits modulating each of them is obtained so that either energy is minimized, rate or margin are maximized. Many of them use the SNR gap approximation for M-QAM signaling, making the algorithm simpler to implement. In some circumstances it may be interesting to use M-ary phase shift keying (M-PSK) instead of M-QAM, e.g. when Golay complementary sequences are used to reduce the PAR (peak-to-average ratio) in OFDM. An approximation is derived for M-PSK similar to the SNR gap of M-QAM, a constant-energy bit loading algorithm is described and its performance is compared to a previously reported algorithm using M-QAM.

This paper provides the results of a complete study about the indoor radio propagation channel at 17 GHz. Wideband parameters, as coherence bandwidth or rms delay spread, and coverage are analyzed for the design of an OFDM-based broadband WLAN. A discussion of some adequate system parameters is also included. The report presents the characterization results as well as a previously developed indoor channel model; both of them have been checked and compared to bibliography results in order to verify their reliability.

Multicarrier modulation techniques are finding growing interest for wireless local area networks (WLANs). Standards, such as Hiperlan type 2 and IEEE 802.11a, have adopted OFDM for transmission of high bit rates in these networks. In this paper we present a simple algorithm for multiuser bit loading in a multicarrier WLAN. The algorithm is based on carrier sense multiple access (CSMA) and it performs up to 50% better than conventional CSMA.