This study aims to present a comparative analysis of existing waveforms for integrated sensing and communication (ISAC) in vehicular environments. A novel multicarrier framework called generalized adaptive spreading modulation (GASM) is proposed for ISAC-enabled vehicular environments. The GASM waveform offers symbol spreading in both time and frequency domains with tunable spreading parameters, which allows the proposed GASM-based waveform to adapt according to the rapid time-frequency variations of the fading channel. This helps to combat the most common system impairments, such as carrier frequency offset (CFO) and symbol timing offset (STO). The GASM scheme is the generalization of various existing waveforms, such as orthogonal frequency-division multiplexing (OFDM), fractional Fourier transform-based OFDM (FrFT-based OFDM), and orthogonal chirp division multiplexing (OCDM). The proposed GASM-based ISAC system is evaluated in terms of average bit error rate (ABER) for the communication and ambiguity function (AF) for sensing capabilities. The performance of the GASM-based ISAC system is found superior as compared to the existing waveforms, i.e., OFDM, FrFT-based OFDM, OCDM, generalized frequency division multiplexing (GFDM), and orthogonal time frequency space (OTFS) modulation.

The fifth-generation (5G) and beyond standards are being challenged by the diverse requirements of modern use cases. Multicarrier modulation techniques are one of the key components of the physical layer (PHY) design, which has immense potential to improve efficiency and reliability. In current state-of-the-art wireless technologies (i.e., NR and IEEE 802.11ax) orthogonal frequency division multiplexing (OFDM) is used which has many disadvantages such as peak-to-average power ratio (PAPR), out-of-band emission (OOBE), and sensitivity to carrier frequency offset (CFO). To overcome these drawbacks several alternate multicarrier modulation techniques are being considered, such as discrete Fourier transform-spread-OFDM (DFT-s-OFDM), generalized frequency division multiplexing (GFDM), and orthogonal time-frequency space (OTFS). In this paper, we develop the physical layer abstraction (PLA) of these candidate multicarrier techniques to evaluate their performance under various use cases and scenarios. The PLA is a commonly used technique to avoid time-consuming PHY simulations in system-level simulators. To improve the accuracy of PLA in different fading conditions, we derive a fitting parameter as a function of the received signal-to-interference-plus-noise ratio (SINR) variance. The validation results show that performance can be accurately estimated through the proposed multicarrier PLA. Moreover, PLA techniques are at least thousands of times faster compared to PHY simulations.

The multi-connectivity is a key enabler for ultra-reliable low-latency communications. To evaluate its performance and suitability to various use cases system-level studies are essential, where the physical layer (PHY) plays an important role. Therefore, PHY modeling is required which is time-intensive and requires highly complex computations. For this purpose, the PHY performance is usually abstracted in terms of signal-to-interference-plus-noise ratio (SINR), also known as physical layer abstraction (PLA). However, due to fading, the symbols inside a packet could have different SINRs which require effective SINR mapping to compute an equivalent SINR. In the context of multi-connectivity, the received SINR depends on all connected links where each link experiences independent fading and on the used link combining technique. As a result, the computation of effective SINR also depends on the combining technique and fading experienced by individual links. To model PHY performance by considering all these effects, we develop PLA for multi-connectivity communications. This includes the computation of received symbols SINR for various link combining techniques and mapping them to effective SINR using enhanced exponential effective SINR mapping (eEESM). Furthermore, a new optimization method is introduced for eEESM to reduce its optimization complexity. Simulation results show that the proposed PLA accurately estimate the performance of different order of multi-connectivity communications under various fading conditions.

In the future, mobility use cases will depend on precise predictions, with Quality of Service (QoS) prediction being a prominent example. This paper presents realistic measurements from today’s vehicles to support robust QoS prediction in the future. Based on a dedicated and controlled measurement campaign, we highlight aspects of the wireless environment and the device characteristics, like the sampling rates, that influence the collected datasets. If not properly handled, such characteristics might hinder the performance of Artificial Intelligence-based algorithms for QoS prediction. Therefore, we also provide insights on dataset characteristics that should be further used to enable easier adoption of AI-based algorithms. New AI-based algorithms should be able to operate in very diverse radio environments with data captured from different devices. We provide several examples that highlight the importance of thoroughly understanding the datasets and their dynamics.

Autocorrelation (AC) is one of the most frequently used methods for initial acquisition. Usually, algorithms that employ a metric based on AC for this purpose, focus on the estimation of synchronization parameters, ignoring the detection performance. This paper analyses the relationship between the structure of the reference sequence that serves to compute the AC and the corresponding attainable detection performance. The distributions of test statistics based on AC for frame detection are derived and validated through simulations in a frequency-flat fading channel. It is shown that the use of AC can outperform, in terms of detection performance, the more complex matched filtering in a certain signal-to-noise ratio region, at the cost of significantly longer required sequences. Besides, we show that a set of sequences, with different periodic structures, can provide the same target detection probability, allowing a flexible sequence design.

In analog receivers, the use of matched filtering with linear frequency modulated signals constitutes an effective means for detecting the presence of an incoming frame as well as for estimating the symbol timing offset (STO). However, in digital receivers, the discrete nature of the corresponding polyphase codes leads, under certain conditions of carrier frequency offsets, to a significant degradation at the output of the matched filter, which, consequently, can result in erroneous STO estimations. Exploiting the symmetry of a reference sequence consisting of a polyphase code and its complex conjugate, this work proposes a new algorithm based on reversed autocorrelation (RC) to improve the accuracy of the STO estimation obtained by matched filtering. On the one hand, the theoretical analysis demonstrates the superiority of matched filtering over RC in terms of detection performance in the low signal-to-noise ratio regime. On the other hand, it is shown by means of numerical evaluation that the RC can efficiently resolve the STO estimation ambiguity.

Matched filtering based on linear frequency modulated (LFM) or chirp signals constitutes a reliable approach for frame detection even in the presence of high carrier frequency offsets (CFOs). However, the use of polyphase codes as discrete versions of LFM signals can lead to strong degradation at the output of the matched filter for certain CFO conditions and sequence lengths, yielding missed detection. This work proposes a new approach to improve the probability of detection achievable with matched filtering for these unfavorable situations. The proposed approach exploits the symmetry of a reference sequence that consists of a polyphase code followed by its complex conjugate with an algorithm based on reversed autocorrelation (RC) and successfully utilizes the robustness of RC against CFO for detection. It is shown that joint detection based on matched filtering and RC can enhance the detection performance significantly compared to conventional matched filtering.

5G and beyond communications systems need to cope with a high degree of heterogeneity in terms of services and requirements. Specially, vehicle-to-everything (V2X) use cases require ultra-reliable and low latency communications (URLLC) under harsh channel conditions. To design an optimal waveform and coding scheme for such use cases is a key challenge. Therefore, new waveforms and coding techniques are need to be investigated. In this paper, we present a comparison of several waveform candidates (orthogonal frequency-division multiplexing (OFDM), discrete Fourier transform-spread-OFDM (DFT-s-OFDM), generalized frequency division multiplexing (GFDM) and orthogonal time frequency space (OTFS)) and coding schemes (convolution, turbo, low-density priority-check (LDPC) and polar) under a common framework. We consider two metrics, i.e. maximum data rates and packet error rate, to evaluate their performance under various fading conditions. The simulation results show that OTFS outperforms all other waveforms in both frequency selective and doubly selective channels. Regarding the coding schemes, turbo codes outperforms all other coding schemes, even though difference with LDPC codes is marginal.

Physical layer abstraction (PLA) is commonly used in system level evaluations to speed up simulations. The accuracy of such evaluations highly depends on the modelling of PLA. Therefore, the main objective of this paper is to model and evaluate the performance of 5G and beyond (5GB) waveforms using PLA techniques. In the existing literature, PLA techniques were mainly used for orthogonal frequency division multiplexing (OFDM), which is commonly used to improve the performance under frequency selective fading. However, it suffers from high peak to average power ratio (PAPR). Therefore, to overcome this, DFT-spread- OFDM (DFT-s-OFDM) is used for uplink communication in the LTE/NR. In future use cases such as vehicle-to-everything (V2X), where high mobility is involved, inter-carrier interference becomes a bottleneck for above waveforms. Therefore, new waveforms are being proposed such as orthogonal time frequency space (OTFS). In the OTFS, data symbols are localized in delay-Doppler domain, and hence delay-Doppler channel impairments (due to mobility) can be easily compensated. To evaluate and compare the performance of above waveforms, we proposed waveforms specific PLA techniques. The proposed PLA techniques are validated though full PHY simulations, and used to compare the performance of different waveforms under frequency selective and doubly selective channels.

An effective approach to enhance the data rate in narrowband power line communication (NBPLC) system is multicarrier modulation based on orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) transmission over multiple power line phases. A key challenge for achieving reliable communication over MIMO-OFDM NBPLC is to mitigate the effects of the correlated non-stationary additive noise. In fact, substantial components of the noise in NBPLC systems exhibit a cyclostationary behavior with a period of half the AC cycle. Moreover, when MIMO transmission is adopted, an important issue that must be considered is the cross-correlation between the different phases. In this work, we propose to classify the cyclostationary noise into three classes, based on the evaluation of second order statistics. In addition, we derive estimates of the probability density functions for each of the three classes and show that while two of them exhibit a Gaussian behavior, the third one has an impulsive behaviour similar to the Middleton class-A noise. Simulation results show that the bit error rate (BER) of MIMO-OFDM NBPLC significantly changes between different classes of noise. Hence, we develop an algorithm for switching data delivery between MIMO-OFDM NBPLC and MIMO-OFDM wireless transmission in unlicensed frequency band that takes into account knowledge of the periodicity of the three classes of noises. The result is a hybrid MIMO-OFDM wireless/NBPLC system, which we refer to as, hybrid MIMO-OFDM WiNPLC. Our simulation results demonstrate BER improvement of the proposed hybrid system over individual MIMO-OFDM NBPLC or MIMO-OFDM wireless systems.

Low altitude aerial base stations onboard unmanned aerial vehicles (UAVs) have recently gained a lot of attention to provide cellular coverage to mobile ground users. In this paper we evaluate the effect of carrier frequency offset (CFO) on the symbol error rate in the downlink of such systems, where a long-term evolution (LTE) compatible time-frequency grid based on generalized frequency division multiplexing (GFDM) is considered. The choice of GFDM as multi-carrier modulation scheme is motivated by its widely proposed application in fifth generation cellular systems and its backward compatibility with LTE. Simulation results are shown for "Better than the Nyquist (BTN)" pulse shaping filters in three different environments: Suburban, Urban and Urban High Rise. The use of BTN pulse shaping filters allows for higher robustness to CFO as compared to base line pulse shaping filer know as root-raised cosine filters for different environments conditions. Simulation results are presented considering realistic air-to-ground propagation conditions generated from the commercial Wireless InSite ray-tracing radio propagation software.

In mission critical wireless sensor networks (WSNs) accurate timestamping of the occurrence of events measured by the sensor nodes is often required together with a high degree of reliability. While precise timestamping requires synchronization of the sensor nodes, reliability is obtained by adding redundancy in all potential single point of failure nodes. In this paper, we focus on a ZigBee-based WSN using two personal area network (PAN) coordinators with different PAN identifiers (IDs) and, for this configuration, we propose a solution where if the primary PAN coordinator goes down, connections are transferred to the other by changing the PAN ID of the nodes. Our proposed solution provides significant gains in terms of recovery speed and timing synchronization accuracy in comparison to a solution that is proposed in the literature.