We propose a scheme to reduce and balance the energy consumption of nodes in dense IoT use cases implemented with LoRa. We study a multiple gateways network with nodes uniformly distributed around each gateway, and restricted to use only short spreading factors. Relays using longer spreading factors, are added to the network infrastructure to forward the nodes transmissions that cannot reach a gateway directly. We find that the impact of the interference added by the relays on the probability of successful transmissions becomes marginal for high density networks. Furthermore, in such dense networks the consumption at the nodes is lowered one order of magnitude with marginal increase in the overall energy consumption of the network. Also, the consumption spread between nodes close and far from the gateway is effectively reduced.

This letter explores key parameters of a massive MIMO system and their impact on energy efficiency at transmission. In particular, the effect of the digital to analog converter resolution and peak to average power ratio reduction techniques are addressed, in the context of practical user location distributions for both line and non line of sight channels. Results show interesting design trade-offs, and highlight the relevance of an accurate model for the user locations for the correct evaluation of the achievable performance.

In this study, the authors propose a novel architecture based on the combination of peak-to-average power ratio (PAPR) reduction with digital beamforming (BF) for mm-wave massive multiple-input multiple-output (MIMO) systems. In order to keep the power amplifiers (PAs) working at the same input back-off thus maximising the system power efficiency, they propose to perform time-domain transmit beam-steering by adding progressive time delays to the signals at each antenna element, while keeping the amplitude weights unitary. They show that these time delays can be obtained with a finite impulse response filter implementation of time-domain fractional delay filter structures such as Lagrange interpolation polynomials. They also introduce an analysis on the PAPR of the interpolated signals, where they derive an upper bound to it and show that its value is similar to that of the signal at the input of the interpolation filters, showing the feasibility of the proposed method. In addition, they present a detailed analysis where they show that a significant reduction in computational complexity is obtained when compared to frequency-domain BF. Simulation results validate that the novel proposed scheme combining PAPR reduction and digital BF offers high-precision beam-steering maintaining reduced PAPR in the delayed signals fed to the antennas.

In this work, we present a novel strategy aiming at obtaining higher energy efficiency in mm-wave digital massive MIMO systems. The proposed approach consists in a joint optimization of time-domain digital beamforming and Tone-Reservation based Peak-to-average Power Ratio (TR-PAPR) reduction. The main idea is to perform broadband beam-steering by adding progressive time delays to the reduced PAPR signals fed to the antennas. These time delays are implemented in digital baseband through time-domain fractional delay filter banks (TDFDFBs). Simulation results show that the increment in MER due to PAPR reduction is maintained for the progressively delayed signals for beam-steering generated by interpolation at the output of the filter bank. As a result, the required power amplifiers (PAs) can all be biased with a lower input back-off (IBO) operation point, leading to significant energy savings while keeping low levels of in-band distortion.

The main goal of this article is to accurately quantity the gain in energy efficiency that can be obtained by combining PAPR reduction techniques with beamforming in the context of massive MIMO communications. To this purpose, we first derive and analyze the expressions of sum capacity, power consumption, and energy efficiency for hybrid, digital and analog beamforming for massive MIMO systems in the millimeter wave frequency range. Then, we use these results to derive and quantity the gain in energy efficiency at system level that can be obtained by combining PAPR reduction for improved power amplifier efficiency with beamforming in massive MIMO systems. In addition, we derive the expressions allowing to determine the optimal amount of antennas M that should be connected to each RF chain in a partially connected hybrid beamforming scheme in order to maximize the systems energy efficiency. Evaluation of the derived expressions clearly show that a noticeable gain in the systems energy efficiency is obtained when PAPR reduction is added, and allows to analyze the advantages and disadvantages of each approach from an energy efficiency point of view.

The development of massive multiple-input multiple-output (MaMIMO)massive multiple-input multiple-output (MaMIMO) techniques is motivated by the requirements of large spectral efficiency and reduced power consumption. The implementation of a large number of antennas offers a large spectral efficiency and link reliability. Moreover, the use of MaMIMO allows scaling down the transmitted power proportionally to the number of antennas used, which may lead to a significant improvement in terms of energy efficiency. Orthogonal frequency division multiplexing (OFDM) in combination with MaMIMO has a considerable potential to obtain very high data rates and high quality of service (QoS). However, MaMIMO systems require a mobile equipped with multiple antennas at the transmitter. This is a challenging issue in mobile devices mostly due to their size, cost, and computing power limitations. In MaMIMO, the radiated power per antenna decreases linearly with the number of antennas. Moreover, the effects of small-scale fading, non-coherent interference, and receiver noise are minimized. However, a massive number of antennas require a separate transceiver chain and power amplifier (PA) for each antenna (unless analog or hybrid analog-digital structures are used for beamforming purposes, in which case the number of RF chains can be reduced). In this situation, the size and costs of the analog front-end become a critical issue. The cost and size optimization implies the use of low-cost components which increase the imperfections that degrade the system performance. In this chapter, MaMIMO system performance, considering front-end RF imperfections and ADC/DAC with limited resolution, is carefully studied. Spectral and energy efficiency for the uplink and downlink scenarios are evaluated to quantify the overall system performance. Finally, low-resolution precoding techniques, antenna coupling, channel non-reciprocity, and channel estimation errors are also addressed.

In contrast to conventional half-duplex (HD) transceivers, a full-duplex (FD) transceiver is able to transmit and receive simultaneously in the same frequency band. The main impediment for FD implementation is the self-interference (SI) caused by the strong coupling of the transmitted signal to the receiver chain. Self-interference is usually mitigated by a combination of antenna cancellation and RF cancelers, both in the analog domain, followed by a digital cancellation technique. After analogue suppression, the SI can be tens of decibels above the signal of interest. Therefore, high-resolution ADCs are required in order to avoid the signal of interest be buried in the quantization noise. Additionally, high-speed ADCs are required to handle the large bandwidth channels envisioned for the next generation of communication systems. Full-duplex systems are very sensitive to different system distortions associated with the analog front-end electronics, since these imperfections significantly limit the SI suppression capability. The main sources of impairments are the nonlinear power amplifiers, phase noise from local oscillators, ADC quantization noise and distortion, and mismatches between I and Q branches of the transceivers. In this chapter, we first introduce a baseband interference model of the imperfections of the system components. Then, we introduce SI cancellation techniques, taking into account phase noise effects, mixer imbalances, and the power amplifier operation point. After that, we determine the necessary ADC requirements for the FD operation. Finally, we analyze the system performance in terms of the energy efficiency and spectral efficiency, considering different system parameters.

Multicarrier systems are widely used due to their high spectral efficiency and robustness against frequency-selective channels. However, the performance of these systems is highly affected by carrier frequency offset (CFO) and phase noise (PN), since the orthogonality between carriers is lost. As these imperfections are mostly related to local oscillator quality and user mobility, low-cost and high-speed applications are critical. The estimation of CFO and phase noise is divided into two steps, acquisition and tracking, where known sequences (or pilot symbols) are used to estimate the parameters at the receiver. The multiuser case is more challenging since the problem is multi-parametric, i.e., it is necessary to estimate the CFO and phase noise of each user. While the compensation of these imperfections is quite simple in the single user case (downlink), it is more elaborated in a multiuser access condition (uplink). Successive interference cancellation or linear suppression techniques are therefore used for CFO and phase noise cancellation in the multiuser case. In this chapter we first describe the effects of the CFO and the phase noise in the system performance, paying special attention to critical applications, such as low-cost unstable oscillators and high-speed vehicles. Then, we introduce several CFO estimation techniques for the downlink (single user case), based on statistical properties of the sequence of pilot symbols. Finally, we present estimation and compensation strategies for the uplink (multiuser case) of orthogonal frequency division multiple access (OFDMA) and multiuser filter bank multicarrier (FBMC), using direct and successive interference cancellation algorithms. The performance of the compensation is evaluated considering high and low mobility scenarios.

In order to reduce the implementation cost, most of the signal processing in the transceiver is carried out in the digital domain. However, the RF front-end components usually represent a significant part of the cost and power consumption, and determine the overall performance of the radio system. In this chapter, we present a review of the most significant front-end impairments that affect the performance of modern wireless communication systems. At the transmitter side, we consider power amplifier (PA) nonlinear distortion and the phase and amplitude imbalances of the mixer. At the receiver, we include the phase noise of the local oscillator, and the analog-to-digital converter (ADC) quantization noise and nonlinear distortion. These models will be used in the following chapters to introduce compensation techniques that improve system performance.

Conventionally, the power amplifier is considered the most power demanding device in a wireless transceiver. Following this assumption, improvements in the power efficiency of the power amplifier (PA) are directly reflected in the power consumption of the overall system. Considering the power consumption of a LTE macrocell base station LTE macro-cell base station , the PA drains around 57% of the total power, while the baseband processing requires only 13%. However, in a femtocell femtocell , the PA consumption represents only 22% of the total power and the portion of the digital block demands 47%. For the case of power limited devices, as a LTE mobile phone, the PA dominates the overall power consumption requiring 44% of the total available power. We can infer from these values that for high/medium power systems, as macrocell base stations, the implementation of linearization techniques or peak-to-average power ratio (PAPR) reduction peak-to-average power ratio (PAPR) reduction methods are mandatory. In that case, their implementation allows to relax the linearity constraints and improve the power efficiency. A substantial energy saving can thus be obtained in that scenario. On the other hand, for low power transceivers low power transceivers , the trade-off between the energy saved by optimizing the PA operation point and the energy required to implement predistortion techniques needs to be carefully evaluated. In this chapter, we address the problem of power consumption in power amplifiers and their effects over energy efficiency and performance of a wireless transceiver. The trade-off between the allowed power amplifier distortion and the system power efficiency is studied. Several nonlinear distortion compensation techniques that can be applied either in the receiver or the transmitter side are introduced and their performance is studied for several scenarios.

Efficient and application-oriented analog-to-digital conversion (ADC) plays a key role on the performance of any communication system. Among the different available architectures, there exists a trade-off between sampling rate and resolution, both also related to the power consumption of the device. In addition, nonlinear distortion can severely reduce the digital dynamic range of the converted signal, thus reducing the effective resolution with the corresponding negative effect on the receiver sensitivity. In this sense, the selection and development of accurate models and compensation strategies are required to restore adequate performance. For example, the complexity of the models and compensation algorithms must also be considered in order to achieve an efficient solution. While ADCs used to sample narrowband signals have little memory effects and allow for simple models and compensation techniques, sampling of broadband signals introduces longer memory effects and more complex nonlinear dynamic models are required (Volterra, piece-wise linear models). Finally, adequate ADC performance metrics and figures of merit have to be carefully chosen to evaluate the quality of the compensation for the application at hand, as well as the measurement set-up and validation tests. In this chapter, we describe several of the available ADC architectures in terms of the achievable resolution and sampling rate, and the trade-off between them. Narrowband as well as wideband modeling and compensation techniques are described and proposed, depending on the particular ADC and the application at hand. Measurement related issues are also discussed.

This chapter summarizes the most relevant topics addressed in the book, including novel interference cancellation techniques, implementation bottlenecks, and open issues that will require future research. The state-of-the-art techniques for increasing energy and spectral efficiency in 5G cellular system are also briefly described.

In this work, we first provide an overview of the state of the art in mismatch error estimation and correction for time-interleaved analog to digital converters (TI-ADCs). Then, we present a novel pilot-based on-line adaptive timing mismatch error estimation approach for TI-ADCs in the context of an impulse radio ultra wideband (IR-UWB) receiver with correlation-based detection. We introduce the developed method and derive the expressions for both additive white Gaussian noise (AWGN) and Rayleigh multipath fading (RMPF) channels. We also derive a lower bound on the required ADC resolution to attain a certain estimation precision. Simulations show the effectiveness of the technique when combined with an adequate compensator. We analyze the estimation error behavior as a function of signal to noise ratio (SNR) and investigate the ADC performance before and after compensation. While all mismatches combined cause the effective number of bits (ENOB) to drop to 3 bits and to 6 bits when considering only timing mismatch, estimation and correction of these errors with the proposed technique can restore a close to ideal behavior. We also show the performance loss at the receiver in terms of bit error rate (BER) and how compensation is able to significantly improve performance.

The presentation provides an overview of the ChimeraTK framework. The project started from a demand for software libraries that provide convenient access to PCIe bus based cards on the MicroTCA.4 platform. Previously called MTCA4U, ChimeraTK is evolving towards a set of frameworks and tools that enable users to build up control applications, while abstracting away specifics of the underlying system. Initially, the focus of the project was the DeviceAccess C++ library and its bindings for Matlab and Python, along with a Qt based client that used DeviceAccess under the hood. However, ChimeraTK has expanded to include more tools like the ControlSystemAdapter, VirtualLab and ApplicationCore. The ControlSystemAdapter framework focuses on tools that enable application code to be written in a middleware agnostic manner. VirtualLab focuses on facilitating testing of application code and providing functional mocks. The ApplicationCore library aims at unifying application interfaces to other tools in the toolkit and improving abstraction. We present an update on improvements to the project and discuss motivations and applications for these new set of tools introduced into the toolkit.

The performance of full-duplex transceivers is highly dependent on their ability to remove the self-interference (SI) that is generated by the simultaneous transmission and reception in the same frequency band. Even after passive isolation and RF cancellation, the magnitude of the residual SI is usually considerably higher than the signal of interest. The resolution of the analog-to-digital converter (ADC) must be rather high to accommodate both the residual SI and the intended signal to allow the digital SI cancellation. Adding to this technical challenge, 5G systems will occupy large signal bandwidths of hundreds of MHz. Thereby, high-speed and high resolution ADCs are required. In order to obtain a reasonable compromise between performance and massive production cost, a time-interleaved ADC (TI ADC) structure is often used. In this paper, we analyze the TI-ADC induced nonlinear distortion on the performance of a full-duplex transceiver. In particular, time-mismatch errors are considered, and in addition, we apply a digital post-processing to mitigate ADC imperfections. Simulation results show that even a slight mismatch in the TI ADC array can severely deteriorate the performance of the whole system. On the other hand, we show that included ADC compensation can restore adequate performance.

We present a novel method for the estimation and correction of mismatch errors in time-interleaved analog-to-digital converters. The estimation of the mismatch errors requires a training signal, but it is efficient, accurate, and effective while keeping low the complexity of the associated algorithm, when compared with other works in the literature. The compensation strategy uses the estimated parameters for offset and gain mismatch error correction, and implements a low-complexity (similar to that of a finite-impulse response filter) Lagrange interpolation filter to correct errors due to timing mismatch, which depends on the dynamics of the input signal. The proposed compensation strategy achieves almost ideal behavior over a wide bandwidth, i.e., only 12% of oversampling is required for an almost complete cancelation of distortion. The method has been tested under severe mismatch conditions (up to 10% timing mismatch and 5% gain and offset mismatch), showing an improvement of over 6 bits in the effective number of bits and 50 dB in the spurious-free dynamic range. In addition, when compared with the available techniques, no limitation on the number of channel converters is introduced since the compensator effectively cancels the distortion even in the presence of large mismatches.