The stochastic geometry-based modeling and analysis of large-scale Integrated Sensing and Communication (ISAC) networks are vital for providing useful ISAC design insights. One important ISAC network characteristic is the sensing and communication (S&C) spatial correlations since the communication users (CUs) are more interested in the sensing target (STs) around them and the base stations prefer to utilize one ISAC signal to serve the CUs and STs close to each other to enable effective S&C coverage. However, most existing works focused on ISAC systems where the locations of CUs and STs are assumed to be independent. This paper bridges this gap by proposing an analytical framework for the ISAC networks where the unified ISAC waveform is modeled with limited main lobe beamwidth and the CUs and STs served by one signal are assumed to be correlatively distributed in spatial domain. Given the model, we first derive some prerequisite auxiliary quantities (i.e., the probability that an ST is served by the main lobe or side lobe, the link distance distribution, etc.) to analyze the network characteristics. Further, the communication/sensing coverage probability, as well as the joint and conditional ISAC coverage probability are analyzed to provide the comprehensive analysis results. Combining the theoretical analysis and simulation results, it verifies the accuracy of the analytical framework and quantifies the impact of the network parameters and spatial correlations on the S&C performance. Moreover, our results reveal how the sensing performance and communication performance are mutually restricted to describe the tradeoffs of S&C performance.

Integrated sensing and communication (ISAC) is a promising technique for future wireless applications that demand both high-quality communication and precise sensing. Characterizing the fundamental tradeoff between sensing and communication (S&C) is essential for guiding cost-effective ISAC designs. However, the exact performance boundary characterizing the tradeoff between the communication rate and the sensing estimation accuracy remains unknown. To tackle this issue, this paper studies the exact Pareto boundary of the Cramér-Rao bound (CRB) and communication rate performance region, as well as the optimal input signal distributions that achieve this boundary. First, the explicit analytical expression of the expected CRB is derived with arbitrary random inputs, which quantify the accuracy of sensing estimation. It is proved that the bound-achieving distribution, which maximizes communication rate while ensuring CRB and power constants, is both timeindependent and circular symmetric. Leveraging these properties, a modified Blahut-Arimoto algorithm is developed based on functional analysis to numerically determine the optimal distribution on the CRB-rate boundary and correspondingly characterize the exact CRB-rate region. Numerical results demonstrate that ISAC systems enable a flexible CRB-rate tradeoff by adjusting the input signal distribution, outperforming separated S&C design benchmark. It is revealed that the communication benefits from greater signal amplitude randomness, while sensing accuracy improves with higher instantaneous power.

This paper investigates an integrated sensing and communication (ISAC) system with finite constellations. Both the problems of performance loss caused by discrete inputs and the conflicting requirements on symbol distribution of sensing and communication (S&C) functionalities are considered. Towards this, a waveform design based on the probabilistic shaping (PS) scheme is proposed, where a base station sends unified signals to estimate a sensing target and communicate with a user simultaneously. The analytical closed-form expressions of the sensing estimation rate (SER) and communication ergodic rate for PS-based ISAC are derived to evaluate the performance of the S&C functionalities, which are found to be mutually influenced by both the probability mass function (PMF) and power scaling factor. Furthermore, the optimal PMF and scaling factor are obtained by the alternative optimization algorithm to maximize SER while preserving communication capability. Simulation results validate the efficiency of our proposed PSbased waveform compared with those of schemes based on other input distributions. Additionally, the performance limit of ISAC systems with finite constellations is numerically obtained, which characterizes the tradeoffs between S&C functionalities.

Integrated Sensing and Communications (ISAC) is emerged as one of the key technologies in next generation wireless systems. However, ISAC systems have been commonly explored neglecting mutual coupling. This paper investigates the mutual coupling exploitation to further improve the performance of ISAC systems. We aim to maximize the sensing beampatern gain by optimizing the tunable loads and the dual-functional beamforming while satisfying the minimum signal-to-interference-plus-noise (SINR) per user and the hardware constraint of the tunable loads. To solve the non-convex problem, we propose a penaltybased iterative algorithm to obtain a stationary point. Specifically, in each iteration we adopt the block coordinate descent (BCD) method where the dual-functional beamforming is obtained by using Lagrange duality, and the tunable loads are solved with closed forms. Numerical results demonstrate the notable gains and effectiveness of the proposed algorithms compared to the baseline schemes. To the best of our knowledge, this is the first study utilizing the MC effect to improve system performance in an ISAC system with tunable loads.

The modeling and analysis of large-scale stochastic MEC systems are of great significance in providing useful design guidelines for practical MEC networks. In most prior works, the users generally adopt the same strategy to select appropriate MEC access points (MAPs), where the fact that the available mobile computing services are different among the randomly distributed users is ignored. To this end, this paper proposes a user-centric cooperative offloading scheme to enable more flexible and efficient user task offloading. Specifically, each user can be served by one or two MAPs based on both the communication performance and computing performance. To evaluate the performance gains acquired from the proposed task offloading scheme, we first derive the service mode assignment probability, link distance distribution, and interference intensity to capture the network characteristics. Further, the moment and the meta distribution of the task transmission performance are analyzed. Based on the above results, we focus on the distribution of the computation workload to evaluate the edge computing service capability. From the analytical and simulation results, it is demonstrated that compared with the non-cooperative offloading scheme, the proposed task offloading scheme not only achieves more reliable and fair task offloading but also increases the computing service capacity.

Integrated sensing and communication (ISAC) has been recognized as a key technology of the next-generation wireless networks. This paper focuses on the ISAC system with discrete signal inputs. Compared with the ISAC systems with continuous inputs in most prior works, it can provide useful insights for ISAC networks with digital modulation at the expense of compensating for the performance gap caused by the finite constellations. To tackle the above problem, a unified analytical framework is proposed to analyze and optimize the ISAC systems with finite constellations in this paper. Based on the analytical framework, both the communication ergodic rate and sensing estimation rate considering non-uniform constellations are derived to characterize the sensing and communication (S&C) performance and quantify the performance gap caused by discrete signals in ISAC networks. To compensate for the performance gap, the probabilistic shaping (PS)-based waveform design is formulated as a multi-objective optimization problem by jointly optimizing the discrete symbol distribution and the power scaling factor for achieving the Pareto-optimal S&C performance. Given the non-convexity of the above problem, an alternating algorithm is proposed to obtain the PS-based waveform. Moreover, the properties of the sensing-optimal and communication-optimal PS-based waveform are analyzed. It is proved that the sensing function prefers amplitude-deterministic signals, and the probabilities of outermost constellations are equal if they are distributed in a circularly symmetric manner. It is indicated that communication functionality requires quasi-Gaussian distribution, which is consistent with the results of our proposed algorithm. Numerical results characterize the tradeoff between S&C and validate the superiority of the proposed PS scheme in comparison with other input distributions.

Covert communication is crucial to ensure the safety of wireless communications in Internet of Things (IoT) systems. In this article, a multiantenna relay is employed to enhance the communication link and avoid the transmission being detected by the multiantenna warder simultaneously. Considering the dynamic fluctuating fading channels of IoT systems, a novel adaptive coordinated direct and relay transmission (ACDRT) scheme is proposed where the relay switches on/off adaptively to maximize the achievable covert rate. The covertness constraint requirements are derived with instantaneous and statistical warder-related channel state information based on the availability of the channel information in practical systems. Since both the direct and the relay links impact the system performance, the optimization problem is formulated, where the beamforming vectors are coupled. A semidefinite relaxation-based line search method is proposed to address this problem. Besides, the globally optimal solutions can be obtained by the proposed method, which is rigorously proved mathematically. In addition, the conditions for achieving a positive covert rate are analyzed with the multiantenna warder. Simulations demonstrate that the performance of the ACDRT is robust to covertness requirements when the positive rate condition holds, and significant covert rate gains can be obtained by the ACDRT with the multiantenna relay compared with the conventional systems.

The stochastic geometry-based modeling and analysis of large-scale mobile edge computing (MEC) networks are vital for the effective configuration of MEC networks. In this paper, we develop a meta-analytical framework for MEC-enabled heterogeneous networks with the communication-computation-aware (CCA) user association mechanism. Compared with the communication-based user association mechanisms in most existing works, the CCA user association mechanism can capture the impacts of network computation capability on the association process between the user and MEC access point, at the expense of dealing with the more complex coupling of communication and computing. Given the need for interference characterization, we first derive the essential prerequisite quantities (i.e., per-tier association probability, link distance distribution, interferer process intensity, etc.) to represent the computation-dependent interference model. Further, the moment and the meta distribution of the task success offloading probability are derived, based on which we investigate the task execution latency performance, including the communication latency, local computing latency, and edge computing latency. By theoretical analysis and simulation results, it is demonstrated that the proposed analytical framework can provide accurate fine-grained network information for the MEC-enabled HetNets. Moreover, we elaborate on the impacts of the edge computation capability on the network performance and reveal important tradeoffs of the performance metrics.

Integrated sensing and communication (ISAC) technique has recently gained significant research interest by supporting dual functions by a unified hardware platform. Traditionally, the ISAC system deemed the sensing and communication functions restricted by each other. In this paper, we demonstrate that a mutual benefit between sensing and communication functions can be achieved for the millimeter-wave ISAC system by efficiently exploiting the common information shared by both functions. Specifically, the sensing estimation can potentially be utilized to improve beamforming accuracy and the communication echo signal can enhance the sensing estimation as well. To demonstrate the mutual performance gain, we evaluate the joint outer bounds of the communication and sensing estimation rates. First, we derive the ergodic communication rate when the communication beamforming is assisted by sensing estimation. The asymptotic characteristic is further explored when the number of antennas approaches to infinity. Then, the closed-form estimation rate is obtained in terms of the Cramér-Rao Bound when the sensing estimation is assisted by communication signals. Numerical results verify the superiority of the mutual benefit when the common information was efficiently exploited by the ISAC BS transceiver. And when the transmission power is equally allocated, there are 10% and 2% gains on the communication rate and the sensing estimation rate simultaneously.

Probabilistic shaping (PS) has been demonstrated as an efficient method to achieve the shaping gain and to approach the Shannon limit in additive white Gaussian noise channels. To narrow the shaping gap caused by the channel fluctuation and the finite blocklength, a novel PS strategy is designed for polar coded communication systems with finite blocklength in Rayleigh flat fading channels. The proposed system transmits the quadrature amplitude modulation symbols and demodulates the received signal through log-maximum-a-posteriori (Log-MAP) detection. The channel capacity is theoretically derived in terms of the mutual information considering the influence of PS and the finite blocklength. Moreover, to solve the non-convex problem that maximizes the channel capacity on the basis of mutual information, an alternating optimization algorithm is proposed. Finally, numerical results indicate that with the optimal probabilistic shaping scheme, the system has 1.7 dB and 0.45 dB gain on the block error rate and channel capacity of the uniform distribution, respectively.