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With the increasing adoption of fifth-generation (5G) networks and wide bandwidth availability, unmanned aerial vehicles (UAVs) should now be practicable to stream and operate at different altitudes and upload incredibly large quantities of data from sensors. We develop a novel intelligent sensing framework (Choi, 2020) so that sensing and communication occur on demand, according to a given query. Our query-based Data Aided Sensing (DAS) approach differs from existing methods as we start with selecting relevant nodes based on the query and then allocating UAVs for collecting measurements. We develop an economical and efficient approach to collect measurements from massive passive sensors, which adaptively minimize the entropy gap while scheduling UAVs to sensors. At the heart of our solution is a mathematical approach for estimating entropy, cost and energy consumption, thereby deploying dynamically optimal UAV-sensor association (e.g., optimizing entropy and employing bipartite graph). Our system has been evaluated with extensive simulations, providing insightful observations and findings.

Non-terrestrial networks (NTNs) have recently attracted elevated levels of interest in large-scale and ever-growing wireless communication networks through the utilization of flying objects, e.g., satellites and unmanned aerial vehicles/drones (UAVs). Interestingly, the applications of UAV-assisted networks are rapidly becoming an integral part of future communication services. This paper first overviews the key components of NTN while highlighting the significance of emerging UAV networks where for example, a group of UAVs can be used as nodes to exchange data packets and form a flying ad hoc network (FANET). In addition, both existing and emerging applications of the FANET are explored. Next, it provides key recent findings and the state-of-the-art of FANETs while examining various routing protocols based on cross-layer modeling. Moreover, a modeling perspective of FANETs is provided considering delay-tolerant networks (DTN) because of the intermittent nature of connectivity in low-density FANETs, where each node (or UAV) can perform store-carry-and-forward (SCF) operations. Indeed, we provide a case study of a UAV network as a DTN, referred to as DTN-assisted FANET. Furthermore, applications of machine learning (ML) in FANET are discussed. This paper ultimately foresees future research paths and problems for allowing FANET in forthcoming wireless communication networks.

Vector Quantized Variational Autoencoder (VQ-VAE) has been regarded as a promising representation of diverse and complex data distributions in deep learning ecosystem. However, its use in a systematic way leveraging existing wireless communications has not been well addressed. In this paper, we explore the VQ-VAE characteristics in a point-to-point wireless communication and modify its training process to design a joint source-channel coding that is robust against noisy wireless channels. With all due respect to the source-channel separation theorem, various factors prevent error-free transmissions of conventional coding schemes in reality. Likewise, the proposed model is not error-free, but it compromises the reliability and complexity of the system. Thus, the proposed model makes the physical/link layer lighter while preserving reliability. It is considered an alternative for further data compression compared to the conventional separated source-channel coding schemes. Our system has been evaluated with extensive simulations, providing insightful observations and findings. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Upon acceptance in IEEE: Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. (Copyright (c) 2015 IEEE.)

Since the 1960s, joint sensing and communication (JSAC) has been proposed as an attractive technique with advantages of enhanced spectral and hardware efficiency along with low latency. However, in those old days, complex transceiver designs hindered the massive adoption of JSAC in many applications. Nevertheless, thanks to advancing wireless technologies in recent years, JSAC has recently attracted substantial attention for a wide range of civil and military applications. In particular, JSAC enables simultaneous sensing and communication functionalities with the full cooperation of both operations in shared resources such as hardware as well as radio resources (i.e., frequency, time, space and so on). Note that sensing functionality is associated with other sub-functionalities of radio-detection-and-ranging (Radar), computation, and localization which are sporadically used terms in the literature. Thus, to generalize the concept and avoid any confusion, we use the term “sensing” in the acronym JSAC as a consistent and general term associated with the other aforementioned sub-functionalities. This paper elaborates on defining sensing and communication operations and then, provides an overview with preliminaries, key latest findings, and state-of-the-art of JSAC. It also explores both existing and emerging Internet of Things (IoT) applications of JSAC. Next, it provides a new classification of JSAC technologies by taking into account not only the existing JSAC technologies but also a diverse range of technologies that allow JSAC to be used for various types of IoT applications. Eventually, this study projects future research directions and challenges of enabling JSAC in IoT.

Enabling ultra-reliable low-latency communication (URLLC) with stringent requirements for transmitting data packets (e.g., 99.999% reliability and 1 millisecond latency) presents considerable challenges in uplink transmissions. For each packet transmission over dynamically allocated network radio resources, the conventional random access protocols are based on a request-grant scheme. This induces excessive latency and necessitates reliable control signalling, resulting overhead. To address these problems, grant-free (GF) solutions are proposed in the fifth-generation (5G) new radio (NR). In this paper, an overview and vision of the state-of-the-art in enabling GF URLLC are presented. In particular, we first provide a comprehensive review of NR specifications and techniques for URLLC, discuss underlying principles, and highlight impeding issues of enabling GF URLLC. Furthermore, we briefly explain two key phenomena of massive multiple-input multiple-output (mMIMO) (i.e., channel hardening and favorable propagation) and build several deep insights into how celebrated mMIMO features can be exploited to enhance the performance of GF URLLC. Moving further ahead, we examine the potential of cell-free (CF) mMIMO and analyze its distinctive features and benefits over mMIMO to resolve GF URLLC issues. Finally, we identify future research directions and challenges in enabling GF URLLC with CF mMIMO.A new version of the paper has been updated on 21/08/2021

Massive multiple input multiple output (mMIMO) assisted grant-free random access (RA) (mGFRA) has been considered a promising RA scheme for future machine-type communication (MTC). In mGFRA, the nature that RA user equipments (UEs) blindly interplay each other in the presence of preamble collision degrades the performance of RA UEs. To address the issue, a mMIMO assisted semi-grant-free RA (mSGFRA) scheme is considered in this paper, where a downlink feedback based on the preamble detection after the preamble phase is introduced. With such a feedback, RA UEs experiencing preamble collision are enforced to keep silent in data-transmission phase, which in turn enhances the performance of RA UEs without experiencing preamble collision. To understand the performance behaviours of mSGFRA, we first analyse the preamble detection performance in mSGFRA and reveal that accurate collided-preamble detection can be achieved with the assistance of mMIMO. Then, we analyse and compare the performance of mSGFRA and mGFRA in terms of success probability. Simulation results validate theoretical analysis and confirm the potential superiority of mSGFRA to mGFRA.

With the increasing adoption of millimeter-waves (mmWave) over cellular networks, outdoor-to-indoor (O2I) communication has been one of the challenging research problems due to high penetration loss of buildings. To address this, we investigate the practicability of utilizing reconfigurable intelligent surfaces (RISs) for assisting such O2I communication. We propose a new notion of prefabricated RIS-empowered wall consisting of a large number of chipless radio frequency identification (RFID) sensors. Each sensor maintains its own bank of delay lines. These sensors which are built within the building walls can potentially be controlled by a main integrated circuit (IC) to regulate the phase of impinging signals. To evaluate our idea, we develop a thorough performance analysis of the RIS-based O2I communication in the mmWave network using stochastic-geometry tools for blockage models. Our analysis facilitates two closed-form approximations of the downlink signal-to-noise ratio (SNR) coverage probability for RIS-based O2I communication. We perform extensive simulations to evaluate the accuracy of the derived expressions, thus providing new observations and findings., Comment: Under review for IEEE transactions on Communications. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the authors

Ambient backscatter communication (AmBC) has been introduced to address communication and power efficiency issues for short-range and low-power Internet-of-Things (IoT) applications. On the other hand, reconfigurable intelligent surface (RIS) has been recently proposed as a promising approach that can control the propagation environment especially in indoor communication environments. In this paper, we propose a new AmBC model over ambient orthogonal-frequency-division-multiplexing (OFDM) subcarriers in the frequency domain in conjunction with RIS for short-range communication scenarios. A tag transmits one bit per each OFDM subcarrier broadcasted from a WiFi access point. Then, RIS augments the signal quality at a reader by compensating the phase distortion effect of multipath channel on the incident signal. We also exploit the special spectrum structure of OFDM to transmit more data over its squeezed orthogonal subcarriers in the frequency domain. Consequently, the proposed method improves the bit-error-rate (BER) performance and provides a higher data rate compared to existing AmBC methods. Analytical and numerical evaluations show the superior performance of the proposed approach in terms of BER and data rate., Comment: 6 pages, accepted in IEEE WCNC, 2020 to appear

Ambient backscatter communication (AmBC) over orthogonal-frequency-division-multiplexing (OFDM) signals has recently been proposed as an appealing technique for low power Internet-of-Things (IoT) applications. The special spectrum structure of OFDM signals provides a range of flexibility in terms of bit-error-rate (BER) performance, data rate, and power consumption. In this paper, we study subcarrier-wise backscatter communication over ambient OFDM signals. This new AmBC is to exploit the special spectrum structure of OFDM to transmit data over its squeezed orthogonal subcarriers. We propose a basis transmission scheme and its two modifications to support a higher data rate with superior BER performance compared to existing methods. The basis scheme can transmit one bit per subcarrier using on-off keying (OOK) modulation in the frequency domain. In the first modification, interleaved subcarrier block transmission model is employed to improve the BER performance of the system in frequency-selective channels. It results in a trade-off between the size of the blocks and data rate. Thus, in the second modification, interleaved index modulation (IM) is employed to mitigate the data rate decrementation of the former modification. It also stabilizes and controls the power of the signal to result in interference reduction for a legacy receiver. Analytical and numerical evaluations provide a proof to see the performance of the proposed method in terms of BER, data rate, and interference., Comment: Under review for IEEE TVT 2020

Time difference of arrival (TDOA) and angle ofarrival (AOA) localization techniques provide satisfactory positioning performance utilizing multiple base-stations (BSs). However, their performance depends on the BSs topology, whichmay restrict localization zones. The significance of the BSstopology increases when the localization needs line-of-sight (LoS)communication and the transmitter utilizes directional antennasfor signal transmission – e.g., unmanned aerial vehicles (UAVs)with directional antennas. In this work, in order to study theimpact of the BSs topology on the performance of the aeriallocalization with LoS communication, we model two well-knownTDOA and one AOA localization techniques with the minimumnumber of required BSs. After analyzing their system model,we derive a closed form expression for the covered area onthe ground by the directional antenna of an aerial transmitter.The covered area determines a region where the BSs should belocated in to be exposed to the LoS communication. From theMATLAB simulation results, we can determine the impact of theBSs topology on the localization accuracy and explain the role ofthe BSs topology in conjunction with the geometric dilution ofprecision (GDOP) and standard deviation (SD) of TDOA/AOAmeasurements. IEEE IEEE Communications Society Peter Kiewit Institute of the University of Nebraska

WOS: 000425726100001 Symbol boundary alignment, with respect to waveform selection, has an important impact on the numerology design for fifth-generation mobile applications. The current symbol boundary alignment, along with orthogonal frequency division multiplexing (OFDM) waveform, strongly suffers from intercarrier interference (ICI) especially in unmanned aerial vehicles (UAV) communications. This happens when the mobility causes Doppler effect which results in loss of orthogonality in OFDM. The available solutions for overcoming the ICI problem suffer from high complexity, low spectral efficiency, and incompatibility with the current radio access technologies. This paper presents a novel symbol boundary alignment, called Low ICI Symbol (LICIS) boundary alignment numerology, to avoid the disadvantages of the available solutions. LICIS utilizes large subcarrier-spacing to reduce the ICI power (e.g., around 5-dB ICI power reduction with subcarrier spacing of 30 kHz in high-speed UAV communications). Moreover, LICIS is based on the same reference clock as local thermal equilibrium (LIE) which guarantees its compatibility with the current LIE numerology. In addition, this approach places only one guard-interval at the end of a sequence of OFDM symbols and creates a subslot. This leads to less overhead and preserves the spectral efficiency. Furthermore, a pre-fast Fourier transform (FFT) multipath channel equalizer is considered for removing the intersymbol interference between the OFDM symbols occurring within the subslot. Only one additional EFT and IEET operations are required for the equalizer which creates an acceptable complexity increment compared to the complexity of other available solutions. Numerical and analytical evaluations show the superior performance of the proposed technique in terms of reliability and spectral efficiency.

In wireless networks, the need for accurate and low complexity localization methods are growing. Although many positioning methods based on signals' time difference of arrival (TDOA) and angle of arrival (AOA) have been proposed, these methods require multiple base stations (BS) and calculations with high complexity. Furthermore, the distance between a target and the BSs are usually larger than the distance between different BSs, which causes geometric dilution of precision (GDP) problem. To circumvent these issues, we propose a novel and linear method for positioning by only one BS. Our method uses both AOA and TDOA of incoming signals and called 'positioning using one BS (PuOB)'. In this method, we take measurements from one BS at different time instances instead of taking measurements from multiple BSs simultaneously. The ability to estimate the mobile transmitter position accurately by using one BS is the highlighted advantage of the PuOB over the conventional methods. The positioning accuracy of PuOB for different BS numbers are presented. According to simulation results, PuOB outperforms TDOA and AOA methods using three and two BSs, respectively.

Cellular systems of fifth generation (5G) require a waveform with flexible guard interval length along with a low power consumption. Different cyclic prefix (CP) durations in long term evolution (LTE) result in loss of orthogonality between transmitted symbols and cause interference. In addition, CP-based waveforms consume more power for CP part. 'Zero tail DFT-spread OFDM' (ZT DFT-s-OFDM) and 'DFT-spread zero word OFDM' (DFT-s-ZW-OFDM) have been proposed recently with flexible guard intervals as a portion of the modulated signal. However, ZT DFT-s-OFDM suffers from intersymbol interference because of imperfect zero tails. On the other hand, although DFT-s-ZW-OFDM has a superior performance in multipath channels, it consumes more power than ZT DFT-s-OFDM. In this paper, we utilize the similarity between the transceivers of these two waveforms to propose an orthogonal hybrid waveform. The hybrid waveform has high flexibility in order to control the symbol power and bit error rate (BER) performance of the system along with having flexible guard interval. The complexity of the proposed hybrid waveform is the same as ZT DFT-s-OFDM and DFT-s-ZW-OFDM. "Aselsan" Inc. HBT-TE-2015-008

Radio frequency identification (RFID) is used for automatic object identification. An RFID system includes several tags attached to the objects. Each tag includes a small circuit and stores an identification. The tags can operate using battery or operate passively without a battery. The reader is in charge of the interrogation of the tags. The anonymous tag estimation problem is referred to the case where the reader is willing to estimate the number of the the tags without individually identifying them. In this paper, we study the anonymous cardinality estimation problem considering the capture effect. The capture effect is referred to the situation where two tags transmit their information simultaneously to the reader. One of the tags is closer to the reader while the other one is farther away. The reader can only hear the transmission of the nearby tag and considers the other transmission as noise. Therefore, instead of a collision, the reader hears a successful transmission. Taking into account the capture effect, we propose two cardinality estimation algorithms by counting the number of successful transmissions and the number of collisions in an interrogation of a reader. We mathematical formulate the probability of capture effect. Using this probability along with the information obtained from the interrogations, we develop our estimators. Our simulation results provide a proof for the accuracy of the estimators and show the performance of the algorithms compared to the other schemes.