Integrated sensing and communication (ISAC) and the Frequency Range 3 (FR3) (upper mid-band) spectrum are among the key enablers of future wireless systems. ISAC promises new sensing functionalities for networks historically designed for communications, while the FR3 spectrum, approximately from 7 to 24GHz, offers large bandwidths and diverse propagation characteristics that significantly extend deployment possibilities. Motivated by the potential synergy between these two paradigms, this work presents an experimental investigation of a multiband ISAC channel in the FR3 range under realistic conditions. Using the Pi-Radio software-defined radio (SDR) platform and superresolution parameter estimation methods, we design a multiband testbed that measures sensing metrics such as the probability of detection (PD), probability of false alarm (PFA), and localization root mean-squared error (RMSE) across sub-bands at 6.5, 8.75, 10, 15, and 21.7 GHz. To analyze how communication performance reacts to environmental dynamics, we introduce the channel update rate gain (CURG), a new metric that quantifies achievable data-rate gains induced by target-dependent channel variations.

This paper introduces two novel algorithms designed to address the challenge of super-resolution sensing parameter estimation in bistatic configurations within communication-centric integrated sensing and communication (ISAC) systems. Our approach leverages the estimated channel state information derived from reference symbols originally intended for communication to achieve super-resolution sensing parameter estimation. The first algorithm, IFFT-C2VNN, employs complex-valued convolutional neural networks to estimate the parameters of different targets, achieving significant reductions in computational complexity compared to traditional methods. The second algorithm, PARAMING, utilizes a parametric method that capitalizes on the knowledge of the system model, including the transmit and receive array geometries, to extract the sensing parameters accurately. Through a comprehensive performance analysis, we demonstrate the effectiveness and robustness of both algorithms across a range of signal-to-noise ratios, underscoring their applicability in realistic ISAC scenarios.

In this study, we perform statistical radar cross section (RCS) analysis for various test targets in an indoor factory at 25-28 GHz, with the goal of determining the best-fit parametric distributions that characterize the target scattering properties to be used in integrated sensing and communication channel modeling standardization. The analysis is conducted based on measurements in quasi-monostatic and bistatic configurations with bistatic angles of 20°, 40°, and 60°. The test targets include unmanned aerial vehicles, an autonomous mobile robot, and a robotic arm. Goodness-of-fit tests validate that the RCS of these targets is best modeled by lognormal and gamma distributions with high statistical confidence. Additionally, we provide a framework for evaluating the near-field (NF), specular-dominant effective bistatic RCS of a rectangular sheet under controlled bistatic geometries. Novel deterministic RCS models are evaluated, incorporating dependencies on the bistatic angle, transmitter-target separation ( 2 m to 10 m ). The results demonstrate that some proposed deterministic RCS models accurately fit the measured data, highlighting their applicability in deterministic RCS characterization in NF bistatic configurations.

Integrated sensing and communication (ISAC) has emerged as a key paradigm for next-generation wireless systems, which allows wireless resources to be used for data transmission and target sensing simultaneously. In this paper, multi-user collaborative target detection in the uplink ISAC system is investigated. To incorporate the target sensing functionality, the system relies on the reuse of uplink signals from the communication users. Specifically, we analyze an uplink multi-user single-input multiple-output (MU-SIMO) communication system with bistatic sensing. Using the channel statistics, we formulate the problem of joint optimal pilot and data power allocation to maximize the uplink ergodic sum rate while meeting communication and sensing quality-of-service (QoS) requirements. To address this non-convex problem, we propose an alternating optimization (AO)-based iterative framework, where the joint power allocation problem is decomposed into two sub-problems. Specifically, the pilot power allocation is optimized using a penalty dual decomposition (PDD)-based gradient ascent algorithm, while the data power allocation is solved via successive convex approximation (SCA). Once the long-term power allocation is determined, the base station (BS) estimates the instantaneous channels using a minimum mean-squared error (MMSE) estimator. Subsequently, based on the estimated instantaneous channel state information (CSI), the receive beamforming for communication users is optimized via another SCA-based method to maximize the sum rate. Meanwhile, the optimal receive beamforming for the target is obtained in closed-form through eigenvalue decomposition (EVD). We provide comprehensive simulation results to analyze the performance of the proposed iterative algorithm and to demonstrate its dependence on different design parameters. Our results also confirm the superiority of the proposed resource allocation approach over conventional benchmark schemes.

The following paper presents a systematic 3rd Generation Partnership Project (3GPP)-compliant characterization of radar cross section (RCS) for indoor factory (InF) objects, including small and mid-sized unmanned aerial vehicles (UAVs), robotic arms, and automated guided vehicles (AGVs). Through measurements in the 25GHz to 28GHz range, we validate the 3GPP standardized log-normal distribution model for RCS for above-mentioned target objects. The 3GPP-complaint RCS parameters obtained for the small-sized UAV are in close agreement (< 1 dB deviation) with 3GPP agreed values. The mid-sized UAVs exhibit higher reflectivity compared to the small-sized UAV due to enhanced specular components attributed to material and lithium-ion battery packs. On the other hand, the robotic arm exhibits dynamic RCS behavior due to mechanical articulation, whereas AGVs show height and motion-dependent reflectivity patterns. Our findings provide empirical validation for RCS characterization for integrated sensing and communication channel modeling in InF environments.

The following paper presents a multi-band sensing channel quality analysis in the upper mid-band, also known as frequency range 3 (FR3). Measurements were conducted at 6.5 GHz, 8.75 GHz, 10 GHz, and 15 GHz, using a setup designed for integrated sensing and communication (ISAC). The sensing channel quality is evaluated using the estimation reliability metric, based on the iterative Levenberg–Marquardt (LM) algorithm. Given the static environment, we also validate a method to handle time-invariant dense multipath components (DMCs). Results show that lower bands enable the detection of more specular components due to lower path loss, but stronger DMC leads to lower estimation SNR. Higher bands provide cleaner estimates despite detecting fewer components. The trade-offs inherent to upper and lower FR3 bands highlight the potential of multi-band ISAC in the FR3 spectrum.

This paper considers an integrated sensing and communication (ISAC) system with monostatic radar functionality using a zero-padding orthogonal frequency division multiplexing (ZP-OFDM) downlink transmission. We focus on ISAC’s sensing aspect, employing an energy-detection (ED) method. The ZP-OFDM transmission is motivated by the fact that sensing can be performed during the silent periods of the transmitter, thereby avoiding self-interference (SI) cancellation processing of the in-band full duplex operation, which is needed for the cyclic prefix (CP)-OFDM. Additionally, we also show that ZP-OFDM can reject nearby clutter interference. We derive the probability of detection (PD) for the ZP and CP-OFDM systems, allowing useful performance analyses. In particular, we show that the PD expressions lead to an upper bound for the ZP-OFDM transmission, which is useful for selecting the best ZP size for a given system configuration. We also provide an expression that allows range comparison between ZP and CP-OFDM, where we consider a general case of imperfect SI cancellation for the CP-OFDM system. The results show that when the ZP size is 25% of the fast Fourier transform size, the range loss of the ZP system range is only 17% larger than the CP transmission.

Integrated sensing and communication (ISAC) aims at enhancing the network functionalities and enabling new applications in the upcoming communications networks. In this paper, we propose two unique word (UW)-based frame designs for bistatic ISAC. The approach consists of replacing the cyclic prefix (CP) with a Zadoff-Chu (ZC)-based sequence. With this approach, the radar receiver does not need to know the data symbols to perform sensing and the data rate is not compromised by the addition of extra pilots. We derive the Cramér-Rao bound (CRB) considering a band-limited system with raised-cosine filtering. Furthermore, we evaluate the performance of a low-complexity fast Fourier transform (FFT)-based radar receiver that performs integer and fine grid delay-Doppler (DD) estimation, using the CRB as a benchmark.

To reuse the scarce spectrum efficiently, a large full-duplex cellular network with integrated sensing and communication (ISAC) is studied. Monostatic detection at the base station (BS) is considered. At the BS, we receive two signals: the communication-mode uplink signal to be decoded and the radar-mode signal to be detected. After self-interference cancellation (SIC), inspired by NOMA, successive interference cancellation (SuIC) is a natural strategy at the BS to retrieve both signals. However, the ordering of SuIC, usually based on some measure of channel strength, is not clear as the radar-mode target is unknown. The detection signal suffers a double path-loss making it vulnerable, but the uplink signal to be decoded originates at a user which has much lower power than the BS making it weak as well. Further, the intercell interference from a large network reduces the channel disparity between the two signals. We investigate the impact of both SuIC orders at the BS, i.e., decoding 1stor detecting 1stand highlight the importance of careful order selection. We find the existence of a threshold target distance before which detecting 1stis superior and decoding 2nddoes not suffer much. After this distance, both decoding 1stand detecting 2ndis superior. Similarly, a threshold UE power exists after which the optimum SuIC order changes. We consider imperfections in SIC; this helps highlight the vulnerability of the decoding and detection in the setup.

In this work, we provide a system level analysis of integrated sensing and communication (ISAC) systems, where a setup with a mono-static dual-functional radar communication base station is assumed. We derive the ISAC signal-to-noise ratio (SNR) equation that relates communication and radar SNRs for different distances. We also derive the ISAC range equation, which can be used for sensing-assisted beamforming applications. Specifically, we show that increasing the frequency and bandwidth is more favorable to the radar application in terms of relative SNR and range while increasing the transmit power is more favorable to communications. Numerical examples reveal that if the range for communication and radar is desired to be in the same order, the ISAC system should operate in mmWave or sub-THz bands, whereas sub-6 GHz allows scenarios where the communication range is of orders of magnitude higher than that of radar.

Driven by the compelling advantages of agility and cost-efficiency inherent in unmanned aerial vehicles (UAV s), this study introduces TANAGERS (emergenT communication for uA vs as flyinG passivE RadarS), an innovative communication-augmented multi-agent reinforcement learning algorithm (MARL) designed for the movement control of UAVs operating as flying passive radars in bistatic integrated sensing and communication scenarios. In this research, we employ the proposed MARL framework to address the sensing signal-to-noise ratio (SNR) maximization problem for targets within a given environment by leveraging signals from base stations, all while taking into account realistic communication channels between pairs of UAV s. Simulation results underscore the significant enhancement brought by our proposed algorithm in radar performance, as measured by the total achievable sensing SNR of the UAV s during their trajectory. The key strength lies in the algorithm's ability to learn a resilient communication protocol that effectively mitigates the stochastic and unreliable nature of channel links between UAV s.

This article examines two chirp spread spectrum techniques specifically devised for low-power wide-area networks (LPWANs) to optimize energy and spectral efficiency (SE). These methods referred to as layered CSS (LCSS) and layered dual-mode CSS (LDMCSS), involves utilizing multiple layers for multiplexing symbols with varying chirp rates. These waveform designs exemplify a high degree of SE compared to existing schemes. Additionally, LDMCSS necessitates a lesser number of layers than LCSS to attain comparable SE, thereby reducing computational complexity. These proposed techniques can employ coherent and non-coherent detection and can be adjusted to achieve various spectral efficiencies by altering the number of multiplexed layers. Unlike our proposed LCSS and LDMCSS, other CSS alternatives for LPWANs cannot provide the same level of flexibility and SE. The performance of these techniques is evaluated in terms of bit error rate under different channel conditions, as well as with phase and frequency offsets.

Various precoders have been recently studied by the wireless community to combat the channel fading effects. Two prominent precoders are implemented with the discrete Fourier transform (DFT) and Walsh-Hadamard transform (WHT). The WHT precoder is implemented with less complexity since it does not need complex multiplications. Also, spreading can be applied sparsely to decrease the transceiver complexity, leading to sparse DFT (SDFT) and sparse Walsh-Hadamard (SWH). Another relevant topic is the design of iterative receivers that deal with inter-symbol-interference (ISI). In particular, many detectors based on expectation propagation (EP) have been proposed recently for channels with high levels of ISI. An alternative is the maximum a-posterior (MAP) detector, although it leads to unfeasible high complexity in many cases. In this paper, we provide a relatively low-complexity computation of the MAP detector for the SWH. We also propose two feasible methods based on the Log-MAP and Max-Log-MAP. Additionally, the DFT, SDFT, and SWH precoders are compared using an EP-based receiver with one-tap FD equalization. Lastly, SWH-Max-Log-MAP is compared to the (S)DFT with EP-based receiver in terms of performance and complexity. The results show that the proposed SWH-Max-Log-MAP has a better performance and complexity trade-off for QPSK and 16-QAM under highly selective channels, but has unfeasible complexity for higher QAM orders.

Integrated sensing and communication (ISAC) aims at enhancing the network functionalities and enabling new applications in the upcoming communications networks. In this paper, we propose two unique word (UW)-based frame designs for bistatic ISAC. The approach consists of replacing the cyclic prefix (CP) with a Zadoff-Chu (ZC)-based sequence. With this approach, the radar receiver does not need to know the data symbols to perform sensing and the data rate is not compromised by the addition of extra pilots. The sensing performance of the UW-based frames is compared with that of orthogonal frequency division multiplexing (OFDM) as well as the pilot-symbol (PS) based radar processing. We derive the Cramér-Rao bound (CRB) considering a band-limited system with raised-cosine filtering. Furthermore, we provide low-complexity fast Fourier transform (FFT)-based radar receivers that perform integer and fine grid multi-target delay-Doppler (DD) estimations. For the integer FFT-based receiver, an upper bound for the outlier probability is derived when the true DD falls outside the integer grid. The results demonstrate that the UW frames exhibit competitive radar performance with PS while having a 16.67% higher data rate for the cases investigated.

Sub-THz communications have been recently considered as an alternative to increase the data rate for the 6th generation (6G) of mobile systems. Since maintaining a reasonable link budget becomes more difficult in higher frequencies, the DFTs-OFDM waveform has been considered as a candidate for sub-THz transmissions, because it has low power-to-average peak ratio (PAPR) in comparison to waveforms with higher PAPR, e.g., orthogonal frequency division multiplexing (OFDM). Additionally, recent channel measurements at 140 GHz have demonstrated that the channel is frequency-selective. This fact motivated us to investigate the DFTs-OFDM link-level performance under an empirical sub-THz channel with the employment of an iterative receiver, since it is known that iterative equalization can mitigate the effects of inter-symbol interference. For this purpose, we consider the minimum mean squared error with parallel interference cancellation (MMSE-PIC) iterative receiver, with convolutional and low-density parity-check (LDPC) codes. The results show that for medium frequency selectivity, LDPC codes provide best performance in terms of frame error rate, but for high selectivity, the convolutional code system has the best performance.

Several waveforms have been recently proposed in the literature as alternatives to orthogonal frequency division multiplexing (OFDM) for frequency selective channels. However, in order to achieve a superior performance, it is necessary to employ iterative equalization. In this paper, we consider the sparse Walsh-Hadamard (SWH) waveform with maximum a-Posterior (MAP) equalization. We show that the inherent structure of the SWH matrix allows a significant reduction in the number of multiplications required for the MAP equalizer implementation. The proposed solutions is compared with the zero padding single carrier (ZP-SC) with MAP equalization. We show that SWH with MAP equalization achieves a good trade-off performance vs complexity compared with ZP-SC. In particular, for 16-QAM under the Proakis C channel, ZP-SC is not even feasible while SWH with MAP equalization has manageable complexity.

Power-domain asynchronous non-orthogonal multiple access (ANOMA) is a novel radio access technique with non-orthogonal resource allocation that enables asynchronous transmissions and has an enhanced spectrum efficiency compared to orthogonal multiple access. In this work, an iterative receiver is derived for linearly modulated waveforms. Orthogonal frequency division multiplexing (OFDM), single-carrier (SC) and orthogonal chirp division multiplexing (OCDM) are investigated. The receiver is based on triangular successive interference cancellation (T-SIC) in combination with a minimum mean square error parallel interference cancellation (MMSE-PIC) detector. It is advantageous to utilize a waveform which spreads the data symbols in the frequency domain as OCDM or SC in order to exploit the multipath diversity in frequency-selective channels. However, it is numerically shown that OCDM performs the best due to its additional time-spreading property, which is desirable for the time-dependent interference that occurs in an ANOMA system. Furthermore, for the considered scenario of two users and four blocks, we show that all the studied waveforms achieve the best performance in terms of block error rate with the derived receiver when the blocks overlap halfway.

Power-domain non-orthogonal multiple access (NOMA) is a promising radio access technique with non-orthogonal resource allocation that provides a greater spectrum efficiency than the conventional orthogonal multiple access (OMA). In this paper, an iterative receiver is derived for NOMA. It is based on soft-information successive interference cancellation (SIC) combined with a minimum mean square error parallel interference cancellation (MMSE-PIC) detector. Orthogonal frequency division multiplexing (OFDM) is usually the typical waveform employed. However, with the proposed receiver design, any linear modulation can be used. In addition to OFDM, single-carrier (SC) and the recently proposed sparse Walsh-Hadamard (SWH) are investigated. The NOMA scheme is analysed in a multi-path fading channel, where two users have different power ratios and waveforms. Simulation results show that mixing OFDM and SWH for a two-user NOMA gives the best performance with low receiver complexity.

In this paper, we investigate three different concepts for robust link-level performance under doubly-dispersive wireless channels, namely, i) channel estimation, ii) cyclic prefix (CP)-free transmission, and iii) waveform design. We employ a unique word-based channel estimation, where we decouple the channel related errors into channel estimation error (CEE) and Doppler error (DE). Then, we show that a trade-off between CEE and DE emerges in the frame design, where the system can be optimized to achieve the minimum composite channel error. Another strategy to improve the link-level performance is to suppress the CP of the sub-blocks. This allows for better channel estimation due to the reduced transmission time, with the penalty of requiring the CP-restoration processing at the receiver. Furthermore, we propose the waveform design based on the equal-reliability criterion (ERC), leading to the block multiplexing-orthogonal chirp division multiplexing (BM-OCDM). This waveform is advantageous in the CP-free transmission mode, where the data symbols have equally distributed interference from adjacent sub-blocks. Our framework is a generalization of the recently proposed orthogonal time frequency space (OTFS), which fails to achieve the ERC. The link-level simulations show that at high modulation and coding scheme, the proposed BM-OCDM provides superior link-level performance than OTFS.

This paper addresses the energy consumption concern of LPWAN by proposing an extension for the LoRa modulation. Conventional LoRa encodes data in the frequency shift of a chirp, our extension consists in encoding additional data in the phase- shift using the PSK modulation, giving rise to the PSK-LoRa. Our motivation is to encode more data per unit of time without performance degradation, such that we have a more energy efficient system. In order to assess the performance of PSK-LoRa, we derive approximate bit error rate and packet error rate expressions, and then we compare against simulation. For instance, both analytical and numerical outcomes demonstrate that QPSK-LoRa has no performance loss in comparison to LoRa, indicating the feasibility of the new scheme.

Spectrum sensing using cooperative power spectral density cancellation (CPSC) over both fast and frequency-selective fading channels has not been investigated yet. We investigate the performance of the newly proposed CPSC method over this severely-impaired Rayleigh channel. We initially compare two approaches to calculate the decision variable in the CPSC algorithm. Then, it is assumed that the fading model can rapidly vary its characteristics over a single sensing interval. The channel model is then also made frequency-selective, by modeling additional resolvable paths. Performance is found by running simulations to find the Receiver Operating Characteristic (ROC) curves under these constraints. Finally, the theoretical achievable throughput of a secondary cognitive user network operating under this scenario is found as another performance criteria. The results reveal that the CPSC method is more sensible to the fast channels when compared to the selective ones. Moreover, it is shown that each scenario has one optimal sensing time, which yields the highest throughput for the secondary network.

In this paper, a new correlated shadowed channel model based on grid points is proposed. It is presented a three-dimensional model capitalizing on the two-dimensional model available in the literature. Additionally, a closed-formula to obtain the theoretical correlation between any two points is derived. In order to show the usefully of the proposed model and as an application example, we provide an important performance analysis related to spectrum sensing for cognitive radio. The effect of correlation in the various aspects of system performance is then investigated. The validity of the analytical results is supported by means of Monte Carlo simulation. The results show that the system performance analysis is more accurate when the proposed model is considered, this conclusion is discussed throughout the paper.