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The use of unmanned aerial vehicle (UAV)- based communication in millimeter-wave (mmWave) frequencies to provide on-demand radio access is a promising approach to improve capacity and coverage in beyond-5G (B5G) systems. There are several design aspects to be addressed when optimizing for the deployment of such UAV base stations. As traffic demand of mobile users varies across time and space, dynamic algorithms that correspondingly adjust the UAV locations are essential to maximize performance. In addition to careful tracking of spatio-temporal user/traffic activity, such optimization needs to account for realistic backhaul constraints. In this work, we first review the latest 3GPP activities behind integrated access and backhaul system design, support for UAV base stations, and mmWave radio relaying functionality. We then compare static and mobile UAV-based communication options under practical assumptions on the mmWave system layout, mobility and clusterization of users, antenna array geometry, and dynamic backhauling. We demonstrate that leveraging the UAV mobility to serve moving users may improve the overall system performance even in the presence of backhaul capacity limitations. [ABSTRACT FROM AUTHOR]

Direct conversion radios are widely recognized as the most appealing approach for reducing the hardware cost as well as power consumption in upcoming communication systems. However, such radios are known to entail gain and phase uncertainties along the analog inphase/quadrature (I/Q) paths. In this paper, we address the effects of the transmitter (TX) and receiver (RX) I/Q errors or mismatches on the improperness of the transmitted and received signals, respectively. We analytically show how the properness of a transmitted signal and the receiver thermal noise can be destroyed, respectively, under the transmitter and receiver I/Q errors, given that the corresponding ideal signals are proper under perfect I/Q balance. Then, we address the spectrum sensing problem in cognitive radio systems through modeling it as a composite binary hypothesis testing task, and apply the likelihood ratio test approach to solve it. To this end, we propose three impropriety-based multiantenna spectrum sensing algorithms under the transmitter and receiver I/Q uncertainties. The principle of invariance is exploited to examine the potential constant false alarm rate (CFAR) behavior of the proposed detectors. We analytically prove that all the proposed sensing methods possess CFAR behavior against the noise variance uncertainty, while only two of them have CFAR property against the receiver I/Q mismatch values. The achievable sensing performance of the proposed methods is then analyzed through extensive numerical experiments, and the devised alternative detectors are mutually compared. Finally, analytical solutions are derived to quantify the improvement/degradation in the effective received signal SNR under I/Q imbalanced radios. [ABSTRACT FROM AUTHOR]

In this communication, the self-interference (SI) channel and the novel enabling techniques for a compact inband full-duplex relay are described and characterized in different operating environments. The full-duplex operation is based on a novel antenna design that uses wavetraps to provide passive isolation of up to 70 dB between the transmit and receive antenna ports. The passive isolation is complemented with novel active RF and digital cancellation stages that further suppress the residual SI to the receiver noise floor. Measurement results of a complete prototype implementation show that the proposed design can achieve an overall SI cancellation performance of over 100 dB even with an ambitious instantaneous bandwidth of 80 MHz. Similar results are obtained both in an anechoic chamber as well as in realistic multipath indoor environments. [ABSTRACT FROM PUBLISHER]

The problem of compressive detection of random subspace signals is studied. We consider signals modeled as \mathbfs=\mathbfH\mathbfx where \mathbfH is an N\times K matrix with K\leq N and \mathbfx\sim \mathcalN\left(\mathbf0K,1,{\sigma }_x^{2}{{\mathbf{I}}}K\right) . We say that signal {\mathbf{s}} lies in or leans toward a subspace if the largest eigenvalue of \mathbfH\mathbfH^T is strictly greater than its smallest eigenvalue. We first design a measurement matrix \mathbf\Phi =\left[\mathbf\Phi s^{T,{\mathbf\Phi }o^{T}\right]}^{T} comprising of two sub-matrices ${{\mathbf{\Phi}} }_{s}$ and ${{\mathbf{\Phi}} }_{o}$ where ${{\mathbf{\Phi}} }_{s}$ projects the signal to the strongest left-singular vectors, i.e., the left-singular vectors corresponding to the largest singular values, of subspace matrix \mathbfH and ${{\mathbf{\Phi}} }_{o}$ projects it to the weakest left-singular vectors. We then propose two detectors that work based on the difference in energies of the samples measured by the two sub-matrices ${{\mathbf{\Phi}} }_{s}$ and ${{\mathbf{\Phi}} }_{o}$ and provide theoretical proofs for their optimality. Simplified versions of the proposed detectors for the case when the variance of noise is known are also provided. Furthermore, we study the performance of the detector when measurements are imprecise and show how imprecision can be compensated by employing more measurement devices. The problem is then re-formulated for the generalized case when the signal lies in the union of a finite number of linear subspaces instead of a single linear subspace. Finally, we study the performance of the proposed methods by simulation examples. [ABSTRACT FROM PUBLISHER]

Floor detection for indoor 3D localization of mobile devices is currently an important challenge in the wireless world. Many approaches currently exist, but usually the robustness of such approaches is not addressed or investigated. The goal of this paper is to show how to robustify the floor estimation when probabilistic approaches with a low number of parameters are employed. Indeed, such an approach would allow a building-independent estimation and a lower computing power at the mobile side. Four robustified algorithms are to be presented: a robust weighted centroid localization method, a robust linear trilateration method, a robust nonlinear trilateration method, and a robust deconvolution method. The proposed approaches use the received signal strengths (RSS) measured by the Mobile Station (MS) from various heardWiFi access points (APs) and provide an estimate of the vertical position of the MS, which can be used for floor detection. We will show that robustification can indeed increase the performance of the RSS-based floor detection algorithms. [ABSTRACT FROM AUTHOR]

In order to support anywhere and anytime services of Beyond 4G networks, new deployment solutions will be required that can cost-effectively address the capacity demand of the future and also offer consistently high bit rates and decent quality of service throughout the network coverage area. In this article we look into an advanced outdoor distributed antenna system (DAS) concept, dynamic DAS, that offers on-demand outdoor capacity in urban areas by dynamically configuring the remote antenna units to either act as individual small cells or distributed nodes of a common central cell. The performance of the investigated DAS solution is evaluated and compared with legacy macrocellular deployment in a dense urban environment. Furthermore, the analysis covers the performance evaluation, mainly from an outdoor perspective. The obtained results indicate superior performance of dynamic DAS concept in terms of coverage and SINR, network capacity and cost-efficiency as compared to legacy macrocellular network deployments. [ABSTRACT FROM AUTHOR]

In this paper, we propose a feature-based method for spectrum sensing of OFDM signals from sub-Nyquist samples over a single band. We exploit the structure of the covariance matrix of OFDM signals to convert an underdetermined set of covariance-based equations to an overdetermined one. The statistical properties of sample covariance matrix are analyzed and then based on that an approximate Generalized Likelihood Ratio Test (GLRT) for detection of OFDM signals from sub-Nyquist samples is derived. The method is also extended to the frequency-selective channels. [ABSTRACT FROM AUTHOR]

To tackle the 1000? mobile data challenge, the research towards the 5th generation of mobile cellular networks is currently ongoing. One clear enabler toward substantially improved network area capacities is the increasing level of network densification at different layers of the overall heterogeneous radio access system. Ultra-dense deployments, or DenseNets, seek to take network densification to a whole new level, where extreme spatial reuse is deployed. This article looks into DenseNets from the perspectives of different deployment strategies, covering the densification of the classical macro layer, extremely dense indoor femto layer, as well as outdoor distributed antenna system (DAS), which can be dynamically configured as a single microcell or multiple independent microcells. Also, the potential of a new indoor-to-outdoor service provisioning paradigm is examined. The different deployment solutions are analyzed from the network area spectral and network energy efficiency perspectives, with extreme densification levels, including both indoor and outdoor use scenarios. The obtained results indicate that dedicated indoor solutions with densely deployed femtocells are much more spectrumand energy-efficient approaches to address the enormous indoor capacity demands compared to densifying the outdoor macro layer, when the systems are pushed to their capacity limits. Furthermore, the dynamic outdoor DAS concept offers an efficient and capacity-adaptive solution to provide outdoor capacity, on demand, in urban areas. [ABSTRACT FROM PUBLISHER]

Communication receivers that utilize I/Q downconversion are troubled by amplitude and phase mismatches between the analog I and Q branches. These mismatches are unavoidable in practice and reduce the obtainable image frequency attenuation to the 20-40-dB range in practical receivers. In wideband multi-channel receivers, where the overall bandwidths are in the range of several megahertz and the incoming carriers located at each other's mirror frequencies have a high dynamic range, the image attenuation of the analog front-end (FE) alone is clearly insufficient. In this paper, two novel blind low-complexity I/Q imbalance compensation techniques are proposed and analyzed to digitally enhance the analog FE image attenuation in wideband direct-conversion receivers. The proposed algorithms are grounded on the concept of circular or proper complex random signals, and they are, by design, able to handle the often overlooked yet increasingly important case of frequency-dependent I/Q mismatches. The first technique is an iterative one, stemming from adaptive filtering principles, whereas the second one is a moment-estimation-based block method. The performance of the algorithms is evaluated through computer simulations, as well as real-world laboratory signal measurement examples in practical multicarrier receiver cases. Based on the obtained results, the proposed compensation techniques can provide very good compensation performance with low computational resources and are robust in the face of different imbalance levels and dynamics of the received signals, as well as many other crucial practical aspects such as the effects of the communications channel and carrier synchronization. [ABSTRACT FROM AUTHOR]

Space-time coded wireless transmission techniques with multiple transmit and receive antennas can provide considerable increases in both the link quality as well as link capacity when compared to ordinary single-antenna techniques. However, multiantenna transmission basically calls for multiple parallel radio implementations, and the resulting link performance is found to be very sensitive to the possible nonidealities of the individual analog radio front-ends. One important practical example is the so-called I/Q imbalance problem related to the amplitude and phase matching of the I/Q branches of the transmitters and receivers. In this paper, we analyze the I/Q imbalance effects in space-time coded transmit diversity system context, in terms of the resulting signal-to-interference ratio as a function of the imbalance properties, assuming the individual transmitter and receiver analog front-ends are based on the so-called direct-conversion radio architecture. The obtained results indicate that the I/Q imbalance effect is fundamentally more challenging in the multiantenna context compared to traditional single-antenna systems. In addition, two digital compensation methods are proposed for combating the resulting signal distortion on the receiver side. The first approach is based on algebraic properties of the derived signal models combined with proper pilot data, while the second one is blind, stemming from the blind signal separation principles. The resulting link-level performance of the proposed algorithms is evaluated using extensive computer simulations. Based on the obtained results, the I/Q imbalance effects can be efficiently compensated using the proposed techniques, the resulting link performance being practically identical to that of the ideal perfectly matched reference case. Furthermore, the proposed methods are also shown to correct for channel estimation errors, in addition to I/Q impairments, and are also reasonably robust against residual carrier offsets. [ABSTRACT FROM AUTHOR]

Due to its simple structure and reduced requirements for radio frequency filtering, the direct-conversion principle has recently gained a lot of interest in radio transceiver design. This paper considers the so-called inphase/quadrature (IJQ) imbalance problem in such structures under the assumption of frequency. selective transmission channel requiring equalization on the receiver side. It will be shown that IJQ imbalance and channel equalization are strongly interdependent, and thus, IJQ mismatch should be taken into account in the equalizer design, and vice versa, particularly with high-order symbol alphabets. Most importantly, the amount of signal distortion caused by transmitter and receiver IJQ imbalances to the equalized received signal will be analytically analyzed through signal-to-interference ratio (SIR) analysis. This gives a quantitative measure to analyze and judge the role of IJQ imbalances in practical communication system design, without having to resort to lengthy data simulations. Furthermore, the analysis shows that imbalance levels that are tolerable in additive white Gaussian noise channels can turn into a serious problem in multipath channels requiring equalization. This gives further motivation and invaluable insight in the overall receiver and system design and in developing digital signal processing-based techniques to mitigate the L/Q imbalance effects on the receiver side. In general, the analytical outcomes and results are verified using extensive computer simulations. [ABSTRACT FROM AUTHOR]

One of the main trends in the evolution of radio receivers and other wireless device is to implement more and more of the receiver functionalities using digital signal processing (DSP). However, due to practical limitations in the analog-to-digital conversion process, some analog signal processing stages are likely to remain also in the continuation. With the ever-increasing demands for the system performance and supported data rates on one side, and the terminal flexibility and implementation costs on the other, the requirements for these remaining analog front-end stages become extremely challenging to meet. Then, one interesting idea in this context is to apply sophisticated DSP-based techniques to compensate for some of the most fundamental nonidealities of the receiver analog front-ends. In this paper, we focus on developing and demonstrating novel digital techniques to mitigate the effects of harmonic and intermodulation distortion in wideband multicarrier or multichannel receivers using adaptive interference cancellation. The approach in general is practically oriented and largely based on analyzing and processing measured real-world receiver front-end signals. The obtained results indicate that the proposed compensation technique can be used to suppress nonlinear distortion due to receiver front-end sections under realistic signaling assumptions [ABSTRACT FROM PUBLISHER]

The general idea of software radio is to develop highly integrated radio transceiver structures with high degree of flexibility and multimode capabilities, achieved through increased role of digital signal processing software in defining the functionalities which have traditionally been implemented with analog RF techniques. This paper explores the software radio concept from the receiver architecture and signal processing points of view, with mainly the wireless terminal application in mind. We first discuss the critical issues in alternative receiver architectures with simplified analog parts and increased configurability. We also introduce certain advanced digital signal processing techniques which could potentially relieve some of the essential problems and pave the way towards DSP-based, highly integrated, and highly configurable terminals. Big emphasis is on efficient digital multirate signal processing methods and complex (I/Q) signal processing. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Presents a study which carried out a general signal analysis of an imbalanced I/Q processing receiver and proposed novel methods for I/Q imbalance compensation using baseband digital signal processing. Interference cancellation-based compensation; Blind source separation-based compensation; Performance analysis.

Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning technologies. Conventionally, PL-based positioning has two phases—fitting a PL model to training data and positioning based on the link distance estimates. However, in both phases, the maximum measurable PL is limited by measurement noise. Such immeasurable samples are called censored PL data and such noisy data are commonly neglected in both the model fitting and in the positioning phase. In the case of censored PL, the loss is known to be above a known threshold level and that information can be used in model fitting and in the positioning phase. In this paper, we examine and propose how to use censored PL data in PL model-based positioning. Additionally, we demonstrate with several simulations the potential of the proposed approach for considerable improvements in positioning accuracy (23–57%) and improved robustness against PL model fitting errors. [ABSTRACT FROM AUTHOR]

This article investigates a full-duplex base station using a generalized frequency division multiplexing (GFDM) transceiver with the radio frequency (RF) impairments including phase noise, carrier frequency offset (CFO) and in-phase (I) and quadrature (Q) imbalance. To fully focus on the RF impairment issue, we study the simple configuration of single uplink user and single downlink user. They both are half-duplex wireless. In the uplink, we study analog and digital self-interference (SI) cancellation and propose a complementary SI suppression method. Desired signal and residual SI powers and signal-to-interference ratio (SIR) are derived in closed form. Similarly, in the downlink, we derive desired signal power, co-channel interference signal power caused by the uplink user and SIR. The RF impairments degrade the efficiency of SI cancellation and affect GFDM more negatively than full-duplex orthogonal frequency division multiplexing (OFDM). Hence, we propose full-duplex GFDM receiver filters for maximizing the SIR for both uplink and downlink transmissions. Finally, the uplink and downlink rates and the uplink-downlink rate region are derived. Significantly, the optimal-filter based GFDM outperforms full-duplex OFDM by 25 dB higher SIR and an uplink rate increase of 500%. [ABSTRACT FROM AUTHOR]

This paper analyzes the performance of linearly precoded time division duplex based multi-user massive MIMO downlink system under joint impacts of channel non-reciprocity (NRC) and imperfect channel state information. We consider a generic and realistic NRC model that accounts for transceiver frequency-response as well as mutual coupling mismatches at both user equipment (UE) and base station (BS) sides. The analysis covers two most prominent forms of linear precoding schemes, namely, zero-forcing (ZF) and maximum-ratio transmission (MRT), and assumes that only the statistical properties of the beamformed channel are used at the UE side to decode the received signal. Under the approximation of i.i.d. Gaussian channels, closed-form analytical expressions are derived for the effective signal to interference and noise ratios (SINRs) and the corresponding capacity lower bounds. The expressions show that, in moderate to high SNR, the additional interference caused by imperfect NRC calibration can degrade the performance of both precoders significantly. Moreover, ZF is shown to be more sensitive to NRC than MRT. Numerical evaluations with practical NRC levels indicate that this performance loss in the spectral efficiency can be as high as 42% for ZF, whereas it is typically less than 13% for MRT. It is also shown that due to the NRC, the asymptotic large-antenna performance of both precoders saturate to an identical finite level. The derived analytical expressions provide useful tools and valuable technical insight, e.g., into calculating the NRC calibration requirements in BSs and UEs for any given specific performance targets in terms of effective SINR or the system capacity bound. [ABSTRACT FROM AUTHOR]

Time-division duplex (TDD)-based massive MIMO systems rely on the reciprocity of the wireless propagation channels when calculating the downlink precoders based on uplink pilots. However, the effective uplink and downlink channels incorporating the analog radio front-ends of the base station (BS) and user equipments (UEs) exhibit non-reciprocity due to non-identical behavior of the individual transmit and receive chains. When the downlink precoder is not aware of such channel non-reciprocity (NRC), system performance can be significantly degraded due to the NRC-induced interference terms. In this paper, we consider a general TDD-based massive MIMO system where frequency-response mismatches at both the BS and UEs, as well as the mutual coupling mismatches at the BS large-antenna system all coexist and induce channel NRC. Based on the NRC-impaired signal models, we first propose a novel iterative estimation method for acquiring both the BS and UE side NRC matrices and then also propose an efficient NRC-aware downlink precoder design which utilizes the obtained estimates. Furthermore, an efficient pilot signaling scheme between the BS and UEs is introduced in order to facilitate executing the proposed estimation method and the NRC-aware precoding technique in practical systems. Comprehensive numerical results indicate substantially improved spectral efficiency performance when the proposed NRC estimation and NRC-aware precoding methods are adopted, compared to the existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper presents a novel digital self-interference canceller for an inband multiple-input-multiple-output (MIMO) full-duplex radio. The signal model utilized by the canceller is capable of modeling the in-phase quadrature (IQ) imbalance, the nonlinearity of the transmitter power amplifier, and the crosstalk between the transmitters, thereby being the most comprehensive signal model presented thus far within the full-duplex literature. Furthermore, it is also shown to be valid for various different radio frequency (RF) cancellation solutions. In addition to this, a novel complexity reduction scheme for the digital canceller is also presented. It is based on the widely known principal component analysis, which is used to generate a transformation matrix for controlling the number of parameters in the canceller. Extensive waveform simulations are then carried out, and the obtained results confirm the high performance of the proposed digital canceller under various circuit imperfections. The complexity reduction scheme is also shown to be capable of removing up to 65% of the parameters in the digital canceller, thereby significantly reducing its computational requirements. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) has been selected as a baseline waveform for long-term evolution (LTE) and fifth-generation new radio (5G NR). Fast-convolution (FC)-based frequency-domain signal processing has been recently considered as an effective tool for transmitter and receiver side subband filtering of OFDM-based waveforms. However, for the original continuous FC-based model, the filtering can, in general, be configured in time-direction only with the granularity of half subframe, corresponding to 7, 14, or 28 symbols with 15kHz, 30kHz, or 60kHz subcarrier spacing, respectively. In this paper, we present a symbol-synchronous FC-processing scheme flexibly allowing filter re-configuration with the time resolution equal to one OFDM symbol while supporting tight carrier-wise filtering for 5G NR in mixed-numerology scenarios with adjustable subcarrier spacings, center frequencies, and subband bandwidths, as well as providing co-existence with LTE. Proposed approach segments each stream of time-domain OFDM symbols into overlapping processing blocks of fixed size. Symbol synchronous processing is achieved by dynamically adjusting the overlap between the processing blocks while aligning the payload part of the processing blocks with the boundaries of the OFDM symbols. The proposed scheme is demonstrated to support the envisioned use cases of 5G NR and provide a flexible starting point for sixth generation (6G) development. [ABSTRACT FROM AUTHOR]

This article presents two novel digital predistortion (DPD) based architectures that jointly mitigate the inphase/quadrature (IQ) modulator impairments and the power amplifier (PA) nonlinear distortion in wireless transmitters. The proposed architectures are multibit cartesian and complex delta-sigma modulator-based joint DPDs, called CDSM-JDPD and CXDSM-JDPD, respectively, which enable using low-cost digital-to-analog converters (DACs) while offering versatile linearization capabilities to combat the coexisting distortions of the PA and the IQ modulator. The proposed approach alleviates the need for reverse modeling and implementation of extra hardware to separately deal with frequency-dependent IQ impairments. Moreover, the CXDSM-JDPD enhances the linearization performance and relaxes the high oversampling ratio (OSR) requirement by quantizing the signal more efficiently. Furthermore, the presented concepts inherently support the use of low-resolution DACs, which offers a tremendous advantage in designing and implementing low-cost and energy-efficient radio transmitters. Extensive set of hardware-in-the-loop RF verification measurements with a commercial PA are provided, including two timely 5G New Radio (NR) scenarios at NR bands n3 and n78, while covering channel bandwidths up to 100 MHz and varying the OSR and the DAC bit resolution. The obtained results demonstrate the excellent linearization capabilities of the proposed solutions and their superiority compared to other DSM-based DPD approaches. [ABSTRACT FROM AUTHOR]

Massive machine type communications (mMTC) is one of the cornerstone services that must be supported by 5G systems. 3GPP has already introduced LTE-M and NB-IoT, referred to as cellular IoT (CIoT), in 3GPP Releases 13, 14, and 15, and submitted these technologies as part of 3GPP's IMT-2020 technology submission to ITU-R. Even though NB-IoT and LTE-M have been shown to satisfy 5G mMTC requirements, it is expected that these CIoT solutions will not address all aspects of IoT and ongoing digitalization, including the support for direct communication between “things” with flexible deployments, different business models, as well as support for even higher node densities and enhanced coverage. In this article, we first describe the Digital Enhanced Cordless Tele-communications (DECT) DECT-2020 standard recently published by ETSI for mMTC communications. We then evaluate its performance and compare it to the existing low-power wide area network solutions, showing that it outperforms those in terms of supported density of nodes while keeping delay and loss guarantees at the required level. [ABSTRACT FROM AUTHOR]

Wireless communication and radars will play a crucial role for autonomous vehicles in the nearest future. However, the blockage caused by surrounding cars can degrade communication performance, while automotive radars are never aimed to operate in such conditions. Therefore, in this paper, the authors propose the concept of near‐ground propagation, reducing the blockage effect in the road traffic conditions. Specifically, the radio waves may freely propagate under the blocking car's bottom if the antennas are placed as low as possible to the road. Based on the measured and modelled results presented in the paper, it may be claimed that near‐ground communication and radar sensing are feasible and may combat even heavily obstructed cases. Nevertheless, some challenges associated with antenna locations were encountered. For example, it was discovered that antenna height at 0.5 m acts less effectively against blockage than at 0.3 m. Next, the 27 dB excess loss at the 0.5 m antenna height in the radar deployment is larger than 17 dB at 0.3 m. In its turn, the higher ground clearance of the blocking vehicle positively affects the near‐ground performance. Additionally, the signal propagation at the grazing angle crucially reduces the relevant losses. [ABSTRACT FROM AUTHOR]

Intermodulation products arise as a result of low noise amplifier (LNA) and mixer non-linearities in wideband receivers. In the presence of strong blockers, the intermodulation distortion can deteriorate the spectrum sensing performance by causing false alarms and degrading the detection probability. We theoretically analyze the impact of third-order non-linearities on the detection and false alarm probabilities for both energy detectors and cyclostationary detectors under front-end LNA non-linearities. We show that degradation of the detection performance due to nonlinearities of both energy and cyclostationary detection is strongly dependent on the modulation type of the blockers. We then propose two DSP-enhanced receiver architectures to compensate the impact of nonlinearities. The first approach is a post-processing technique which compensates for nonlinearities effect on the test statistic by adapting the sensing time and detection threshold. The second approach is a pre-processing method that compensates by correcting received samples prior to computing the test statistic. This approach is based on adaptively estimating the intermodulation distortion, weighting it by a scalar constant and subtracting it from the subband of interest. We propose a method to adaptively compute the optimal weighting coefficient and show that it depends on the power and modulation of the blockers. Our results show that the pre-processing sample-based compensation method is more effective and that clear dynamic range extension can be obtained by using intermodulation compensation without resorting to increasing the sensing time. We also study the impact of uncertainties about the knowledge or estimates for nonlinearity parameters. [ABSTRACT FROM PUBLISHER]

For the development of highly integrated, flexible and low-cost cognitive radio (CR) devices, simple transceiver architectures, like direct-conversion receiver, are expected to be deployed and provide viable radio frequency (RF) spectrum sensing solutions for practical implementation. Yet, this can be very challenging task especially if spectrum sensing and down-conversion are conducted over multiple RF channels simultaneously for improved efficiency in channel scans. Then, the so-called dirty RF problem that degrades link performance of traditional transmission systems starts to be influential from spectrum sensing perspective as well. The unavoidable RF impairments, e.g., oscillator phase noise in direct-conversion receiver, could generate crosstalk between multiple channels that are down-converted simultaneously, and thus considerably limit the spectrum sensing capabilities. Most of the existing spectrum sensing studies in literature assume an ideal RF receiver and have not considered such practical RF hardware problem. In this article, we study the impact of oscillator phase noise on energy detection (ED) based spectrum sensing in multi-channel direct-conversion receiver scenario. With complex Gaussian primary user (PU) signal models, we first derive the detection and false alarm probabilities in closed-form expression. The analytical results, verified through extensive simulations, show that the wideband multi-channel sensing receiver is very sensitive to the neighboring channel crosstalk induced by oscillator phase noise. More specifically, it is shown that the false alarm probability of multi-channel energy detection increases significantly, compared to the ideal RF receiver case. The exact performance degradation depends on the power of neighboring channels as well as statistical characteristics of the phase noise in the deployed receiver. In order to prevent such performance degradation in spectrum identification, an enhanced energy detection technique is proposed. The proposed technique calculates the leakage power from neighboring channels for each channel and improves the sample energy statistics by subtracting this leakage power from the raw values. An analytical expression is derived for the leakage power which is shown to be a function of power spectral levels of neighboring channels and 3-dB bandwidth of phase noise process. Practical schemes for estimating these two quantities are discussed. Extensive computer simulations show that the proposed enhanced detection yields false alarm rates that are very close to those of an ideal RF receiver and hence clearly outperforms classical energy detection. [ABSTRACT FROM AUTHOR]

Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands. In this article, we address the radio-based sensing and environment mapping prospects with specific emphasis on the user equipment (UE) side. We first describe an efficient $\ell _1$ -regularized least-squares (LS) approach to obtain sparse range–angle charts at individual measurement or sensing locations. For the subsequent environment mapping, we then introduce a novel state model for mapping diffuse and specular scattering, which allows efficient tracking of individual scatterers over time using interacting multiple model (IMM) extended Kalman filter and smoother. Also the related measurement selection and data association problems are addressed. We provide extensive numerical indoor mapping results at the 28 GHz band deploying OFDM-based 5G NR uplink waveform with 400 MHz channel bandwidth, covering both accurate ray-tracing based as well as actual RF measurement results. The results illustrate the superiority of the dynamic tracking-based solutions, compared to static reference methods, while overall demonstrate the excellent prospects of radio-based mobile environment sensing and mapping in future mm-wave networks. [ABSTRACT FROM AUTHOR]

In this article, we study closed-loop digital predistortion (DPD) systems and associated learning algorithms. Specifically, we propose various low-complexity approaches to estimate and manipulate the inverse of the input data covariance matrix (CM) and combine them with the so-called self-orthogonalized (SO) learning rule. The inherent simplicity of the SO algorithm, combined with the proposed solutions, allows for remarkably reduced complexity in the DPD system while maintaining similar linearization performance compared to other state-of-the-art methods. This is demonstrated with thorough over-the-air (OTA) mmW measurement results at 28 GHz, incorporating a state-of-the-art 64-element active antenna array, and very wide channel bandwidths up to 800 MHz. In addition, complexity analyses are carried out, which together with the measured linearization performance demonstrates favorable performance–complexity tradeoffs in linearizing mmW active array transmitters through the proposed solutions. The techniques can find application in systems where the power amplifier (PA) nonlinearities are time-varying and thus frequent or even constant updating of the DPD is required, good examples being mmW adaptive antenna arrays as well as terminal transmitters in 5G and beyond networks. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the sensitivity of orthogonal frequency-division multiplexing waveforms to the joint distortion effects of coexisting nonidealities in the implementation of transceiver radio frequency (RF) electronics, combined also with time variations of the multipath radio channel. To cope with the challenge in evaluation of error rates under non-Gaussian joint interference, we propose a semianalytical method for the evaluation of the uncoded symbol-error rate for an arbitrary rectangular quadrature amplitude modulation as subcarrier modulation. This allows deriving maximum tolerable impairment levels for RF circuits such that the link detection error rate is kept at a target level. [ABSTRACT FROM PUBLISHER]

Piecewise behavioral models are commonly adopted for modeling and linearization of RF power amplifiers (PAs) that exhibit strong amplitude-dependent nonlinear distortion characteristics, as global polynomial approximations tend to underperform in such scenarios. In this article, we consider a new piecewise model for PAs based on the mixture of experts (ME) approach, which builds on a probabilistic model that allows the different submodels to cooperate—as opposed to operating in an independent fashion that is commonly the case in existing reference methods. We first introduce the ME framework theory while also extend it such that it can be applied to model complex baseband signals and nonlinearities. Then, we show how the ME model allows overcoming some of the intrinsic shortcomings that existing piecewise behavioral models commonly exhibit, which translates into improved modeling accuracy and improved linearization performance. Furthermore, the extension of the ME approach to a tree-structured regression model, referred to as the hierarchical ME model, is also introduced and shown to provide further performance improvements over the basic ME approach. The proposed solutions are validated with extensive RF measurements, covering both PA direct modeling and digital predistortion (DPD)-based linearization, on a gallium nitride (GaN) load-modulated balanced PA, on a GaN Doherty PA, and on a class AB GaN high electron mobility transistor PA, while being compared against several state-of-the-art piecewise methods. The results demonstrate that the ME framework-based models outperform the state of the art. [ABSTRACT FROM AUTHOR]

This work investigates the secrecy capability of energy harvesting based overlay cognitive networks (EHOCNs). To this end, we assume that a message by a licensed transmitter is relayed by an unlicensed sender. Critically, the unlicensed sender uses energy harvested from licensed signals, enhancing the overall energy efficiency and maintaining the integrity of licensed communications. To secure messages broadcast by the unlicensed sender against the wire-tapper, full-duplex destinations – unlicensed recipient and licensed receiver – jam the eavesdropper at the same time they receive signals from the unlicensed sender. To this effect, we derive closed-form formulas for the secrecy outage probability, which then quantify the security performance of both unlicensed and licensed communications for EHOCNs with jamming-assisted full-duplex destinations, namely EHOCNwFD. In addition, optimum operating parameters are established, which can serve as essential design guidelines of such systems. [ABSTRACT FROM AUTHOR]

Balancing between power amplifier (PA) linearity and power efficiency is one of the biggest implementation challenges in radio communication transmitters. Among various linearization methods, the feedforward linearization technique is a fairly established principle offering a good tradeoff between linearity and power-efficiency even under wideband operation. Moreover, adaptive techniques for such linearizer have been proposed in literature to track parameter changes in the main PA and other circuitry. Among those, least mean squares (LMS) method for adapting signal cancellation loop (SCL) and error cancellation loop (ECL) coefficients is an attractive low-complexity alternative. In this paper, we carry out extensive closed-form performance analysis of the achievable intermodulation distortion (IMD) reduction of the overall LMS-adaptive feedforward linearizer, as a function of the used step-sizes and essential waveform statistics. Such analysis is currently missing from the state-of-the-art literature. Both memoryless nonlinearities and Wiener–Hammerstein type PA memory models are studied for which IMD suppression expressions are derived. Comprehensive computer simulations are also provided to illustrate the accuracy of the analysis when practical OFDM waveforms are used. Design examples are given as well where the analysis results are used to choose proper linearizer step-sizes to meet given transmitter spectral mask specifications. [ABSTRACT FROM PUBLISHER]

This article discusses the applicability of quadrature ΣΔ modulator (QΣΔM) based analog-to-digital (A/D) conversion in cognitive radio (CR) receivers. First, unavoidable in-phase/quadrature (I/Q) mismatch effects, limiting the dynamic range, are analyzed in closed-form in the case of a first-order modulator. In addition, using the derived analytical converter model, it is shown that notching the signal transfer function (STF) of the modulator at the mirror frequencies of the desired signals will effectively cancel the I/Q imbalance induced mirror-frequency interference in case of the modulator feedback mismatch. In practice, such STF design is easy to implement within the existing converter circuitry, as will be demonstrated in this article. The latter part of the article proposes a novel complex multiband QΣΔM scheme, particularly aimed for the CR receivers. This multiband scheme allows parallel reception of scattered frequency chunks in the CR context and is stemming from the additional degrees of freedom in noise transfer function (NTF) design, provided by the QΣΔM principle. Here multiple noise shaping notches on distinct frequencies are effectively realized through proper design of complex NTF. The modulator structure also allows flexible reconfigurability of the notches with straightforward parameterization of the modulator transfer functions. When combined with the above mirror-frequency rejecting STF design, the concept is demonstrated and proved effective and robust against I/Q imbalances using practical radio signal simulations in realistic received signal conditions. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel digital predistorter structure for joint mitigation of frequency-dependent power amplifier (PA) and in-phase and quadrature (I/Q) modulator impairments in direct-conversion radio transmitters. The predistorter is based on an extended parallel Hammerstein structure, yielding a predistorter that is fully linear in the parameters. In the parameter estimation stage, the indirect learning architecture is utilized. The proposed technique is the first technique in the literature to consider the joint estimation and mitigation of frequency-dependent PAand I/Q modulator impairments. Extensive simulation and measurement analysis is carried out to verify the operation and efficacy of the proposed predistortion structure. It is shown that the adjacent channel power ratio is increased by more than 20 dB in all experiments when using the proposed method, and that the performance of the reference techniques is clearly exceeded. [ABSTRACT FROM AUTHOR]

The κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the κ−μ/ inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the η−μ/ inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-average distance. As a result, it is shown that the κ−μ/ inverse gamma composite fading model provides a better fit compared to the η−μ/ inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the η−μ/ inverse gamma composite fading model outperforms the κ−μ/ inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter η is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical. [ABSTRACT FROM AUTHOR]

Modern millimeter-wave automotive radars are employed to keep a safe distance between vehicles and reduce the collision risk when driving. Meanwhile, an on-board radar module is supposed to operate in the line-of-sight condition, which limits its sensing capabilities in intersections with obstructed visibility. Therefore, this paper investigates the scheme with passive reflector, enabling the automotive radar to detect an approaching vehicle in the non-line-of-sight (blind) urban intersection. First, extensive radar measurements of the backscattering power are carried out with the in-house assembled millimeter-wave radar equipment. Next, the measured data is employed to calibrate an accurate analytical model, deduced and described in this paper. Finally, the analytical models are deployed to define the optimal parameters of the radar scheme in the particular geometry of the selected intersection scenario. Specifically, it is found that the optimal angular orientation of the reflector is 43.5°, while the 20 m curvature radius shows better performance compared to a flat reflector. Specifically, the curved convex shape increases scattering power by 20 dB in the shadow region and, thus, improves the detection probability of the vehicle, approaching the blind intersection. [ABSTRACT FROM AUTHOR]

In time division duplexing based mobile networks, under certain atmospheric ducting conditions, the uplink reception may be interfered by the downlink transmissions of remote base-stations (gNBs) located hundreds of kilometers away. This paper addresses such remote interference problem in a 5G new radio (NR) macro deployment context. Specifically, two potential reference signal (RS) designs for remote interference management (RIM) are described. The first signal structure, denoted as the one OFDM symbol (1OS) based RIM-RS, is building on the channel state information reference signals of 5G NR. The second candidate is referred to as the two OFDM symbol based RIM-RS design, which builds on the design principles of LTE RIM-RS. The achievable detection performance is evaluated by introducing enhanced receiver algorithms together with three feasible propagation delay based gNB grouping and corresponding RIM-RS transmissions schemes. The performance results in terms of the receiver processing gain highlight that the improved detection algorithm assures sufficient performance to detect the remote interference for both RIM-RSs with all evaluated frequency domain comb-like patterns. The benefit of grouping corresponding RIM-RS transmissions from gNBs located on the same area is greater when using same frequency domain resources per transmitted sequence in practical interference scenarios. Furthermore, applying a common base sequence for all gNBs within a group allows to identify the group based on detected sequence and enables adaptive RIM mitigation schemes. On the other hand, it is shown that the 1OS RIM-RS provides smaller overhead and can be frequency multiplexed with the physical downlink shared channel, which opens up the possibility of using gNB group wise 1OS RIM-RS also for UE interference measurements. [ABSTRACT FROM AUTHOR]

Beamforming is one of the key technologies for achieving the high performance criteria in various modern and future wireless communications systems, in particular at the millimeter wave frequencies. In order to avoid or reduce the large signaling overhead and corresponding latency related to beam-training procedures, location-based beamforming utilizing available position information has been proposed. In this paper, by using the available position probability density function of a receiving device, we derive and analyze the capacity of a beamformed radio link, without and with beam-sweeping based beam training. Through the analysis, we show that by adjusting the beamforming and/or beam-training parameters appropriately, the radio link capacity can be optimized with respect to the prevailing positioning accuracy, and thus optimal utilization of radio resources is achieved with minimal radio access latency. [ABSTRACT FROM AUTHOR]

Highly directional millimeter-wave (mmW) connectivity – especially in industry-grade scenarios with complex and unpredictable device mobility – requires a certain degree of structural redundancy in the network, which can be provided by utilizing multi-connectivity mechanisms. To lower the coordination complexity and overhead of tracking multiple directional beams, mmW networks can retrieve and leverage timely positioning information. In this paper, we develop a holistic framework for the co-design of networking and positioning in industrial 5G mmW deployments with multi-connectivity capabilities. In particular, we propose a flexible two-stage positioning solution – mindful of information uncertainty – that relies upon the 5G NR system design and can be seamlessly integrated into the mmW cellular infrastructure with reasonable overheads. We reproduce a typical 5G mmW network deployment featuring dissimilar device mobility patterns and assess the performance of the proposed architecture. In particular, we evaluate the precision of our positioning and base station orientation estimation methods as well as analyze the impact of the proposed scheme on the system-level performance. Our numerical results demonstrate that the proposed solution yields highly accurate position estimates and significantly improves the average network spectral efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we present a class of cascaded nonlinear models for complex-valued system identification, aimed at baseband modeling of nonlinear radio systems. The proposed models consist of serially connected elementary linear and nonlinear blocks, with the nonlinear blocks implemented as uniform spline-interpolated look-up tables (LUT) and the linear blocks as FIR filters. Wiener, Hammerstein, and Wiener-Hammerstein models are built, and simple but efficient gradient based adaptive learning rules are derived for all the models. This approach leads to remarkably simple solutions in terms of computational complexity, making the techniques suitable for real-time implementation. The proposed methods are then applied to full-duplex self-interference cancellation and digital predistortion in various real-life scenarios. First, evaluations with measured data from an in-band full-duplex prototype working at 2.4 GHz ISM band show that the algorithms are capable of obtaining similar cancellation performance as existing state-of-the-art solutions, regardless of the clearly reduced complexity. Second, a mmW active antenna array working at 28 GHz center frequency is digitally predistorted with the proposed solutions. The unwanted emissions and nonlinear distortion are suppressed to similar levels as with other state-of-the art solutions, and the corresponding linearity specifications are fulfilled in all cases, while the processing complexity is again drastically reduced. [ABSTRACT FROM AUTHOR]

In this article, we study digital predistortion (DPD)-based linearization with a specific focus on millimeter-wave (mmW) active antenna arrays. Due to the very large-channel bandwidths and beam-dependence of nonlinear distortion in such systems, we present a closed-loop DPD learning architecture, lookup table (LUT)-based memory DPD models, and low-complexity sign-based estimation algorithms such that even continuous DPD learning could be technically feasible. To this end, three different learning algorithms—sign, signed regressor, and sign–sign—are formulated for the LUT-based DPD models such that the potential rank deficiencies, experienced in earlier methods, are avoided while facilitating greatly reduced learning complexity. The injection-based LUT DPD structure is also shown to allow for low numbers and reduced dynamic range of the involved LUT entries. Extensive RF measurements utilizing a state-of-the-art mmW active antenna array system at 28 GHz are carried out and reported to validate the methods, incorporating very wide channel bandwidths of 400 and 800 MHz while pushing the array close to saturation. In addition, the processing and learning complexities of the considered techniques are analyzed, which, together with the measured linearization performance figures, allows to assess the complexity–performance tradeoffs of the proposed solutions. Overall, the results show that efficient mmW array linearization can be obtained through the proposed methods at very low complexity. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public and civil applications, such as goods delivery, medicine, surveillance, and telecommunications. For the latter, UAVs with onboard communication equipment may help temporarily offload traffic onto the neighboring cells in fifth-generation networks and beyond (5G+). In this paper, we propose and evaluate the use of UAVs traveling over the area of interest to relieve congestion in 5G+ systems under spontaneous traffic fluctuations. To this end, we assess two inherently different offloading schemes, named routed and controlled UAV ‘bridging’. Using the tools of renewal theory and stochastic geometry, we analytically characterize these schemes in terms of the fraction of traffic demand that can be offloaded onto the UAV ‘bridge’ as our parameter of interest. This framework accounts for the unique features of millimeter-wave (mmWave) radio propagation and city deployment types with potential line-of-sight (LoS) link blockage by buildings. We also introduce enhancements to the proposed schemes that significantly improve the offloading gains. Our findings offer evidence that the UAV ‘bridges’ may be used for efficient traffic offloading in various urban scenarios. [ABSTRACT FROM AUTHOR]

Industrial automation has created a high demand for private 5G networks, the deployment of which calls for an efficient and reliable solution to ensure strict compliance with regulatory emission limits. While traditional methods for measuring outdoor interference include collecting real-world data by walking or driving, the use of unmanned aerial vehicles (UAVs) offers an attractive alternative due to their flexible mobility and adaptive altitude. As UAVs perform measurements quickly and semiautomatically, they can potentially assist in near-real-time adjustments of the network configuration and fine-tuning its parameters, such as antenna settings and transmit power, as well as help improve indoor connectivity while respecting outdoor emission constraints. This article offers a firsthand tutorial on using aerial 5G emission assessment for interference management in nonpublic networks by reviewing the key challenges of UAV-mounted radio scanner measurements. In particular, we outline the challenges of practical assessment of the outdoor interference originating from a local indoor 5G network while discussing regulatory and other related constraints, and address practical methods and tools while summarizing the recent results of our measurement campaign. The reported proof of concept confirms that UAV-based systems represent a promising tool for capturing outdoor interference from private 5G systems. [ABSTRACT FROM AUTHOR]

Future mobile networks will enable new use cases, requiring further enhanced data rates, latency, coverage, capacity, and reliability. In this article, to emphasize sustainable energy consumption and improved device battery lifetime, the concept, benefits, and challenges of utilizing wake-up radio-based access in 5G networks are reviewed and discussed. To this end, the operating principle and associated wake-up signal structures are first reviewed, together with the corresponding power consumption and buffering delay trade-offs. Then the applicability of wake-up methods at mmWave bands and beamforming systems is addressed and highlighted. Additionally, an energy-efficient mobility management procedure for wake-up radio-based devices is described and demonstrated, utilizing narrowband uplink reference signals. Overall, the article provides an overview of wake-up-based access in 5G systems as a promising power-saving mechanism, and discusses the associated prospects, benefits, and challenges. [ABSTRACT FROM AUTHOR]

In this paper, the performance of the cooperative cognitive radio network with the amplify-and-forward protocol is studied when the relay uses a nonlinear power amplifier (NLPA). Furthermore, taking the pulse shaping filter for the data signal into account, the power of the adjacent channel interference (ACI) to the primary users (PUs) caused by the spectral regrowth of the relay output signal is analytically calculated. Moreover, two compensation techniques are proposed which are implemented at the destination receiver to deal with the in-band nonlinear interference. The first technique is based on the calculation of the distorted signal constellation to enhance the performance of the demodulator. The second technique is feedforward compensation at the receiver. The bit error rate (BER) expressions for both techniques are presented. The ACI resulting from the spectral regrowth due to the relay NLPA is investigated by the simulation and numerical studies, and then, the BER performance degradation at the destination node and the performance improvement resulting from the proposed compensation methods are evaluated. Since the ACI confines the transmit power due to the interference power constraint of the PU, the achievable BER of the secondary user (SU) is studied. The simulation results show that the feedforward compensation technique has better BER performance than the modified constellation based approach. [ABSTRACT FROM AUTHOR]

This article presents a power amplifier (PA) design, which consists of eight class-D PA units on a single 28-nm CMOS die and a coupled-line power combiner on printed circuit board. The PA utilizes tri-phasing modulation, which combines polar and outphasing components in a way that eliminates linearity-degrading effects of multilevel outphasing while maintaining the back off efficiency.Each PA unit contains a cascoded output stage with a 3.6-V supply voltage, and multilevel operation is enabled by ON/OFF logic circuitry. Our analysis shows that the choice of power-combiner type is vital for reducing PA supply and ground ripple and thus ensuring reliable operation.Accordingly, the power combiner is implemented with extended Marchand baluns, which consist of input transmission lines and coupled-line sections. Unlike the original Marchand balun, our new topology is feasible for implementation under the layout restrictions caused by the multiple-unit PA on a single die.Measurement results show the PA achieving a peak output power of 29.7 dBm with a 34.7% efficiency, and operation with aggregated Long Term Evolution (LTE) signals at 1.7-GHz carrier frequency is verified with bandwidths up to 100 MHz. [ABSTRACT FROM AUTHOR]

Recently, the concept of wake-up radio based access has been considered as an effective power saving mechanism for 5G mobile devices. In this article, the average power consumption of a wake-up radio enabled mobile device is analyzed and modeled by using a semi-Markov process. Building on this, a delay-constrained optimization problem is then formulated, to maximize the device energy-efficiency under given latency requirements, allowing the optimal parameters of the wake-up scheme to be obtained in closed form. The provided numerical results show that, for a given delay requirement, the proposed solution is able to reduce the power consumption by up to 40% compared with an optimized discontinuous reception (DRX) based reference scheme. [ABSTRACT FROM AUTHOR]

This article studies the processing principles, implementation challenges, and performance of orthogonal frequency-division multiplexing (OFDM)-based radars, with particular focus on the fourth-generation Long-Term Evolution (LTE) and fifth-generation (5G) New Radio (NR) mobile networks’ base stations and their utilization for radar/sensing purposes. First, we address the problem stemming from the unused subcarriers within the LTE and NR transmit signal passbands and their impact on frequency-domain radar processing. In particular, we formulate and adopt a computationally efficient interpolation approach to mitigate the effects of such empty subcarriers in the radar processing. We evaluate the target detection and the corresponding range and velocity estimation performance through computer simulations and show that high-quality target detection as well as high-precision range and velocity estimation can be achieved. In particular, 5G NR waveforms, through their impressive channel bandwidths and configurable subcarrier spacing, are shown to provide very good radar/sensing performance. Then, a fundamental implementation challenge of transmitter–receiver (TX–RX) isolation in OFDM radars is addressed, with specific emphasis on shared-antenna cases, where the TX–RX isolation challenges are the largest. It is confirmed that from the OFDM radar processing perspective, limited TX–RX isolation is primarily a concern in the detection of static targets, while moving targets are inherently more robust to transmitter self-interference (SI). Properly tailored analog/RF and digital SI cancellation solutions for OFDM radars are also described and implemented and shown through RF measurements to be key technical ingredients for practical deployments, particularly from static and slowly moving targets’ point of view. [ABSTRACT FROM AUTHOR]

Providing high-capacity radio connectivity for high-speed trains (HSTs) is one of the most important use cases of emerging fifth generation (5G) New Radio (NR) networks. In this article, we show that 5G NR technology can also facilitate high-accuracy continuous localization and tracking of HSTs. Furthermore, we describe and demonstrate how the NR network can utilize the continuous location information for efficient beam management and beamforming, as well as for downlink Doppler precompensation in the single-frequency network context. Additionally, with particular focus on millimeter-wave networks, novel concepts for low-latency inter-carrier interference (ICI) estimation and compensation, due to residual Doppler and oscillator phase noise, are described and demonstrated. The provided numerical results at 30 GHz operating band show that sub-meter positioning and sub-degree beam direction accuracies can be obtained with very high probabilities on the order of 95-99 percent. The results also show that the described Doppler precompensation and ICI estimation and cancellation methods substantially improve the throughput of the single-frequency HST network. [ABSTRACT FROM AUTHOR]

In this correspondence paper, we study the peak-to-average power ratio (PAPR) problem in orthogonal frequency-division multiplexing systems. In conventional clipping and filtering based PAPR reduction techniques, clipping noise is allowed to spread over the whole active passband, thus degrading the transmit signal quality similarly at all active subcarriers. However, since modern radio networks support frequency multiplexing of users and services with highly different quality-of-service expectations, clipping noise from PAPR reduction should be distributed unequally over the corresponding physical resource blocks (PRBs). To facilitate this, we present an efficient PAPR reduction technique, where clipping noise can be flexibly controlled and filtered inside the transmitter passband, allowing to control the transmitted signal quality per PRB. Numerical results are provided in 5G new radio mobile network context, demonstrating the flexibility and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]