We introduce a new analytical framework, developed based on the spatial network calculus, for performance assessment of Low Earth Orbit (LEO) satellite networks. Specifically, we model the satellites' spatial positions as a strong ball-regulated point process on the sphere. Under this model, proximal points in space exhibit a locally repulsive property, reflecting the fact that intersatellite links are protected by a safety distance and would not be arbitrarily close. Subsequently, we derive analytical lower bounds on the conditional coverage probabilities under Nakagami-$m$ and Rayleigh fading, respectively. These expressions have a low computational complexity, enabling efficient numerical evaluations. We validate the effectiveness of our theoretical model by contrasting the coverage probability obtained from our analysis with that estimated from a Starlink constellation. The results show that our analysis provides a tight lower bound on the actual value and, surprisingly, matches the empirical simulations almost perfectly with a 1 dB shift. This demonstrates our framework as an appropriate theoretical model for LEO satellite networks.

The directional RTS/CTS mechanism of mm-wave Wi-Fi hardly resolves the hidden terminal problem perfectly. This paper proposes cross-link RTS/CTS under multi-link operation (MLO) to address this problem and introduces a novel point process, named the generalized RTS/CTS hard-core process (G-HCP), to model the spatial transceiver relationships under the RTS/CTS mechanism, including the directional case and the omnidirectional case. Analytical expressions are derived for the intensity, the mean interference, an approximation of the success probability, and the expected number of hidden nodes for the directional RTS/CTS mechanism. Theoretical and numerical results demonstrate the performance difference between two RTS/CTS mechanisms. The cross-link RTS/CTS mechanism ensures higher link quality at the cost of reduced network throughput. In contrast, the directional RTS/CTS sacrifices the link quality for higher throughput. Our study reveals a fundamental trade-off between link reliability and network throughput, providing critical insights into the selection and optimization of RTS/CTS mechanisms in next-generation WLAN standards.

This paper extends the classical network calculus to spatial scenarios, focusing on wireless networks with differentiated services and varying transmit power levels. Building on a spatial network calculus, a prior extension of network calculus to spatial settings, we propose a generalized framework by introducing regulations for stationary marked point processes. The regulations correspond to two key constraints: the total transmit power of all transmitters within a spatial region and the cumulative received power at a receiver, which we refer to as ball regulation and shot-noise regulation, respectively. Then we prove the equivalence of ball regulation and shot-noise regulation for stationary marked point processes and establish a universal lower bound on the performance of all network links under these constraints. This framework is applicable to diverse network scenarios, as demonstrated by the analysis of performance guarantees for networks with multi-class users. In addition, we propose an SINR-based power control scheme adapted to user traffic, which ensures differentiated quality of service (QoS) for different user classes.

This paper studies the performance of large-scale wireless networks with finite queue lengths, an aspect that has been largely overlooked in previous studies focusing on single-link or single-queue models. By modeling packet transmission in networks with finite-length queues and employing meta distribution analysis, we derive precise expressions for delay and packet loss probability. Our findings show that when queue capacities are limited, the transmission success probability significantly influences packet loss behavior. Specifically, a sharp increase in packet loss occurs when the transmission success probability drops below a critical threshold. While increasing queue length does not mitigate packet loss in suboptimal transmission conditions, it can notably enhance network performance under typical scenarios. This study provides important insights for optimizing resource allocation in large-scale wireless networks, emphasizing the need to balance queue length and transmission success probability for better efficiency.

This paper presents a novel analysis of the directional RTS/CTS handshake mechanism using stochastic geometry, treating its impact as a thinning process in a spatial point process. We introduce unique thinning procedures based on the cosine antenna pattern, offering a more accurate representation of directional transmission in millimeter-wave networks. Through these models, we derive expressions for the intensity of concurrent transmitter processes and the mean interference. Our analysis provides key insights into how mean interference varies with system parameters such as antenna configuration and protection distance. Specifically, numerical results demonstrate that increasing the number of transmit antennas reduces interference, though diminishing returns are observed as the number of antennas grows.

This paper investigates the dynamics of spatio-temporal interference correlations in wireless networks, focusing on the interplay between node spatial distribution and interference patterns. The study employs analytical frameworks such as the Matérn hard-core point process (MHCP) and clustering models, revealing that spatial clustering typically enhances positive interference correlation, while spatial rejection mechanisms inherent to MHCP induce negative correlation. Notably, the analysis extends to various temporal traffic models, highlighting distinct interference correlation behaviors between temporally correlated and independent traffic scenarios. The novel contribution of this work lies in deriving advanced mathematical formulations to quantify the interference correlation coefficient, which uncover the non-monotonic relationship between correlation and network parameters like node density and burst traffic duration. These insights provide a deeper understanding of interference dynamics, offering valuable guidelines for optimizing network performance and reliability, particularly in the design of next-generation wireless systems.

This paper introduces a new stochastic geometry-based model to analyze the Request-to-Send/Clear-to-Send (RTS/CTS) handshake mechanism in wireless local area networks (WLANs). We develop an advanced hard-core point process model, termed the dual-zone hard-core process (DZHCP), which extends traditional hard-core models to capture the spatial interactions and exclusion effects introduced by the RTS/CTS mechanism. This model integrates key parameters accounting for the thinning effects imposed by RTS/CTS, enabling a refined characterization of active transmitters in the network. Analytical expressions are derived for the intensity of the DZHCP, the mean interference, and an approximation of the success probability, providing insight into how network performance depends on critical design parameters. Our results demonstrate that the Type II RTS/CTS mechanism significantly reduces mean interference by introducing additional protection regions, effectively mitigating the impact of nearby interferers. Compared to CSMA-based schemes, it achieves a lower mean interference level while maintaining a comparable or higher active node density.

Mobile computing devices are supporting higher information transmission and processing rates. However, the massive amount of information transmitted and processed also means that a vast amount of heat is produced. Due to the constraints of safety and portability, the problem of overheating is becoming a main challenge for mobile computing devices to achieve their ideal performance. Compared to studies on improving the quality of wireless communications and mobile computing, little attention has been paid to the temperature and its direct impact on the computing performance of the device. In this paper, we propose the heat transfer model of the processor of a mobile computing device based on thermodynamics. Considering Landauer’s principle, the maximum computing rate of the processor is derived. Moreover, the performance of devices adopting multi-processor is evaluated, where each processor works periodically to complete the computing task. The conditions for stable computing and the thermodynamic advantage of multi-processor are given. Based on the evaluation, an optimization method is proposed to lower the average temperature of the processor, and simulation results show that the maximum computing rate can be improved up to 20.9%.

This paper investigates the spatio-temporal interference correlation in wireless networks, emphasizing the impact of spatial node rejection modeled by two types of Matern Hard-Core Point Processes (MHCP). We explore how the spatial rejection inherent to MHCP types I and II shapes interference patterns, with a particular focus on the negative correlation effects on network performance. Our study further examine the temporally correlated traffic model, which reveals significant insights into how temporal correlation affects interference. By deriving expressions for the interference correlation coefficient, we illustrate the critical role of path loss and spatial rejection parameters. The work contributes to a refined understanding of interference dynamics in networks modeled by MHCP and guides the strategic development of efficient wireless systems in the presence of correlated traffic.

This paper presents an in-depth analysis and optimization of energy efficiency in wireless networks enhanced by Reconfigurable Intelligent Surfaces (RISs). Our investigation centers around RIS-assisted communication systems, particularly in scenarios lacking a direct link. Utilizing stochastic geometry as our analytical tool, we delve into the dynamics of coverage probability, which serves as a foundation for deriving insights into spectrum efficiency and, ultimately, energy efficiency. A novel aspect of our research is the examination of how the accuracy of the phase shift matrix in RIS impacts energy efficiency. We offer strategies for adjusting this matrix to optimize energy usage. Furthermore, our study reveals a finding: adjusting the number of RISs, while maintaining constant total power consumption, can help get maximum energy efficiency. This work not only advances the theoretical understanding of RIS in wireless networks but also provides practical guidelines for their efficient implementation, marking a contribution to the development of energy-efficient wireless communication technologies.

Efficient channel feedback is crucial for optimizing Wireless Local Area Networks (WLANs), where traditional channel sounding often incurs substantial overhead, primarily from beamforming feedback. This work presents an innovative Adaptive Quantization Model (AQM) leveraging Artificial Intel - ligence and Machine Learning (AIML) to optimize the channel sounding feedback mechanism. The AQM intelligently adjusts feedback quantization levels, achieving a balanced quantization accuracy while minimizing resource consumption. It dynamically selects the optimal number of quantization bits for feedback angle vectors, tailored to current channel states and device operational parameters. Notably, our method achieves a signif - icant reduction in overhead, safeguarding Packet Error Rate (PER) and thus ensuring the integrity of communication qual - ity. Through rigorous simulations, the AQM has demonstrated marked improvements in throughput and a notable decrease in channel sounding overhead. The findings also suggest potential avenues for incorporating such AIML - based approaches into future WLAN protocol standards, charting a course for more sophisticated and resource - efficient wireless communications.

The spatio-temporal correlation of interference is an important factor in affecting the performance of wireless networks. In this paper, we study how the spatio-temporal correlation of traffic affects the correlation of interference, in which the spatial correlation of traffic is captured by using Poisson cluster process (PCP) to characterize the spatial attraction, while the temporal correlation is described by correlated arrival and process of packets. The closed-form expressions to quantitatively describe the interference correlation caused by spatio-temporal correlated traffic are derived. Our results reveal that the spatial aggregation of traffic leads to an increase in interference correlation compared with spatially independent traffic. If the traffic is temporally independent, the interference correlation decreases with the increase of the distance between two receivers or the cluster size. For temporally intra-correlated traffic, when increasing the transmission probability, the interference correlation first increases and then decreases when increasing the cluster size. Considering the queuing process of the traffic, the interference correlation increases with the increase of packet arrival rate when all queues are stable.

Massive Internet of Things (IoT) is an important application scenario for the next-generation mobile communication systems. The channel estimation is crucial for the performance of massive wireless access in IoT. However, when the number of terminals is large, the huge pilot overhead may seriously increase the burden of the wireless access system. Therefore, reducing the pilot overhead while ensuring the accuracy of channel estimation is an important challenge for massive wireless access systems. In this article, we propose a massive wireless access mechanism, which greatly reduces the pilot overhead and improve the energy efficiency (EE) of terminals. Based on the self-similarity of fractal channels, the channel-state information (CSI) of a subset of terminals is sampled to estimate the CSI of all terminals, thereby reducing the pilot overhead and solving the shortage of pilot resources in massive wireless access systems. Meanwhile, the optimal transmission power of terminals based on CSI can save the energy consumption of terminals in IoT. Compared with the traditional algorithm, simulation results indicate that the proposed massive wireless access mechanism improves the EE of terminal by 340% and reduces 70% of the pilot overhead.

The evolution of the Industrial Internet of Things (IIoTs) greatly increases the volume of data generated by the connected IIoT devices. IIoT data are playing an increasingly important role in various industrial sectors. IIoT data sharing helps enterprises make better production decisions and respond to market changes timely. However, the distrust among IIoT entities and IIoT entities’ distrust of data-sharing platforms may hinder the realization of data sharing. In this article, a decentralized IIoT data-sharing scheme based on blockchain and edge computing is proposed. A Proof of Storage and Transmission (PoST) consensus mechanism is proposed to meet data storage and transmission requirements of data owners in IIoT data-sharing networks. Based on the manufacture ties of data owners, shared data request probabilities are derived. The IIoT data sharing interactions between data owners and edge devices are modeled as a multiple-leader and multiple-follower Stackelberg game. The alternating direction method of multipliers (ADMMs) algorithm is used to obtain the optimal IIoT data sharing solutions in a distributed manner. Simulation results show that compared with the cooperative scheme, the total profit of edge devices is maximally increased by 59%, and the total utility of data owners is maximally increased by 52%.

A fine-grained analysis of the cache-enabled networks is crucial for system design. In this paper, we focus on the meta distribution of the signal-to-interference ratio for the cache-enabled networks where the locations of the base stations are modeled as a Poisson point process. With the application of the random caching and the random discontinuous transmission schemes, we derive the moments of the conditional successful transmission probability, the exact meta distribution and its beta approximation by utilizing stochastic geometry. The closed-form expressions of the mean and variance of the local delay (i.e., the jitter) are also derived. We then consider the maximization of the mean successful transmission probability and the minimization of the average system transmission delay by jointly optimizing the caching probability and the BS active probability. Finally, the numerical results demonstrate the superiority of the proposed optimization schemes over the existing caching strategies and reveal the impacts of the key network parameters on the cache-enabled networks in terms of successful transmission probability, successful transmission probability variance, meta distribution, mean local delay and jitter.

In this paper, we focus on the local delay for the cache-enabled networks where the locations of the base stations (BSs) are modeled as a Poisson point process (PPP). With the application of the random caching and the random discontinuous transmission (DTX) schemes, we derive the closed-form expression of the mean local delay. We then consider the minimization of the mean local delay by jointly optimizing the caching probability and the BS active probability. Finally, the numerical results demonstrate the superiority of the proposed optimization schemes over the existing caching strategies and reveal the impacts of the key network parameters on the cache-enabled networks in terms of mean local delay.

The vision for smart city imperiously appeals to the implementation of Internet-of-Things (IoT), some features of which, such as massive access and bursty short packet transmissions, require new methods to enable the cellular system to seamlessly support its integration. Rigorous theoretical analysis is indispensable to obtain constructive insight for the networking design of massive access. In this paper, we propose and define the notion of massive and sporadic access (MSA) to quantitatively describe the massive access of IoT devices. We evaluate the temporal correlation of interference and successful transmission events, and verify that such correlation is negligible in the scenario of MSA. In view of this, in order to resolve the difficulty in any precise spatio-temporal analysis where complex interactions persist among the queues, we propose an approximation that all nodes are moving so fast that their locations are independent at different time slots. Furthermore, we compare the original static network and the equivalent network with high mobility to demonstrate the effectiveness of the proposed approximation approach. The proposed approach is promising for providing a convenient and general solution to evaluate and design the IoT network with massive and sporadic access.

In recent years, the conventional degrees of freedom in frequency and time have been fully used. It is difficult to further improve the performance of communication systems with such degrees of freedom. Orbital angular momentum (OAM), which provides a new degree of freedom for millimeter-wave (mmWave) wireless communication systems, has been recognized as a key enabling technique for future mobile communication networks. By combining OAM beams that have theoretically infinite and mutually orthogonal states with the generalized spatial modulation (GSM) strategy, a new OAM-GSM mmWave wireless communication system is designed in this paper. A bit error rate (BER) model of the OAM-GSM system is established based on channel flip precoding. The channel capacity, energy efficiency, and BER of the proposed OAM-GSM mmWave wireless communication system are simulated. Numerical results show that, compared with traditional GSM systems, the OAM-GSM system has more complex transmission and reception mechanisms but the channel capacity and maximum achievable energy efficiency are increased by 80% and 54%, respectively, and the BER drops by 91.5%.

Emergence of various types of wireless applications has brought about fast growing and diversified traffic in cellular networks. To gain a comprehensive understanding of the influences caused by the differentiated and dynamic traffic is vital for the design of the next-generation wireless networks. In this paper, we develop a mathematical framework for meta-distribution analysis by utilizing queueing theory and stochastic geometry to capture the spatial (geographical location) and temporal randomness (queue status) of traffic. We derive the${k}$-th moment of the conditional successful transmission probability (STP) and the closed-form expressions of the meta distribution for the cell-center users (CCUs) and the cell-edge users (CEUs), respectively. The results are further extended to obtain the analytical expression of the meta distribution by taking the temporal random arrival of traffic into consideration. Moreover, the mean local delays for the CCUs and CEUs are derived. Finally, the impact of key network parameters on the meta distribution and the corresponding mean local delay is investigated.

In this paper, the real-time deployment of unmanned aerial vehicles (UAVs) as flying base stations (BSs) for optimizing the throughput of mobile users is investigated for UAV networks. This problem is formulated as a time-varying mixed-integer non-convex programming (MINP) problem, which is challenging to find an optimal solution in a short time with conventional optimization techniques. Hence, we propose an actor-critic-based (AC-based) deep reinforcement learning (DRL) method to find near-optimal UAV positions at every moment. In the proposed method, the process searching for the solution iteratively at a particular moment is modeled as a Markov decision process (MDP). To handle infinite state and action spaces and improve the robustness of the decision process, two powerful neural networks (NNs) are configured to evaluate the UAV position adjustments and make decisions, respectively. Compared with heuristic algorithm, sequential least-squares programming and fixed UAVs methods, simulation results have shown that the proposed method outperforms these three benchmarks in terms of the throughput at every moment in UAV networks.

The traffic in wireless networks has become diverse and fluctuating both spatially and temporally due to the emergence of new wireless applications and the complexity of scenarios. The purpose of this paper is to quantitatively analyze the impact of the wireless traffic, which fluctuates both spatially and temporally, on the performance of the wireless networks. Specially, we propose to combine the tools from stochastic geometry and queueing theory to model the spatial and temporal fluctuation of traffic, which to our best knowledge has seldom been evaluated analytically. We derive the spatial and temporal statistics, the total arrival rate, the stability of queues and the delay of users by considering two different spatial properties of traffic, i.e., the uniformly and non-uniformly distributed cases. The numerical results indicate that although the fluctuation of traffic (reflected by the variance of total arrival rate) when the users are clustered is much fiercer than that when the users are uniformly distributed, the unstable probability is smaller. Our work provides a useful reference for the design of wireless networks when the complex spatio-temporal fluctuation of the traffic is considered.

Emerging wireless applications starve for the realization of the ultra-reliable and low-latency communication (URLLC). The reliability and latency requirements of URLLC for a specific single link have been explored extensively, but a comprehensive evaluation of the URLLC in a large-scale wireless network is still lacking. In this paper, by using the point process theory we evaluate the probability that the delay and reliability requirement of a typical URLLC user can be satisfied in the large-scale wireless network. This probability is also the ratio of users with satisfactory delay and reliability in the wireless network. In order to improve the performance of URLLC, we propose two retransmission policies, corresponding to time diversity and frequency diversity, in which the retransmissions are silenced randomly to reduce the interference correlation in different frames so to reduce the effect of correlations between different retransmissions. Simulation and numerical results reveal that both of the proposed two retransmission policies improve the performance of URLLC, and the retransmission policy of frequency diversity is better than that of the time diversity.

The conventional outage in wireless communication systems is caused by the deterioration of the wireless communication link, i.e., the received signal power is less than the minimum received signal power. Is there a possibility that the outage occurs in wireless communication systems with a good channel state? Based on both communication and heat transfer theories, a power-consumption outage in the wireless communication between millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) base stations (BSs) and smartphones has been modeled and analyzed. Moreover, the total transmission time model with respect to the number of power-consumption outages is derived for mmWave massive MIMO communication systems. Simulation results indicate that the total transmission time is extended by the power-consumption outage, which deteriorates the average transmission rate of mmWave massive MIMO BSs.

To satisfy the requirement of the fifth generation (5G) mobile communications that offers an ultra high data rate of 100Mbps to 1Gbps anytime and anywhere, the coordinated multipoint (CoMP) technique is proposed to mitigate intercell interference to improve the coverage of high data rate services, cell-edge throughput, and system capacity. However, the joint transmission (JT) CoMP technique is difficult to be applied in practice due to the critical time synchronization for multiple coordination links and the bottleneck of backhaul capacity and radio resource at each small cell base stations (SBSs). Moreover, since the coordination SBSs in the conditional scheme are entirely separate from each other, different time of arrivals at the user cause the severe time synchronization problem. The anisotropic propagation environment in the urban scenario makes the implementation condition even worse. To tackle these issues, we propose a novel JT-CoMP scheme with the anisotropic path loss model to minimize the network backhaul traffic subject to the constraints on the radio resource and the differences in time of arrivals. Simulation results demonstrate that the proposed distance-resource-limited CoMP scheme can obtain the maximum achievable rate with the minimum network backhaul traffic, compared with existing schemes.

An increasing number of low-power Internet of Things (IoT) devices will be widely deployed in the near future. Considering the short-range communication of low-power devices, multihop transmissions will become an important transmission mechanism in IoT networks. It is a crucial for low-power devices to transmit data over long distances via multihop in a low-delay and reliable way. The small-world characteristics of networks indicate that the network has an advantage of a small average shortest-path length (ASL) and a high average clustering coefficient (ACC). In this article, a new IoT routing mechanism considering small-world characteristics is proposed to reduce the delay and improve the reliability. The ASL and ACC are derived for the performance analysis of small-world characteristics in IoT networks based on Cayley graphs. Besides, the reliability and delay models are proposed for small-world IoT based on Cayley graphs (SWITCH). The simulation results demonstrate that SWITCH has lower delay and better reliability than that of conventional nearest neighboring routing (NNR). Moreover, the maximum delay of SWITCH is reduced by 50.6% compared with that by NNR.

To understand the spatial deployment of base stations (BSs) is the first step to analyze the performance of cellular networks and further design efficient networking protocols. Poisson point process (PPP), which has been widely adopted to characterize the deployment of BSs and established the reputation to give tractable results in the stochastic geometry analyses, usually assumes a static BS deployment density in homogeneous PPP (HPPP) models or delicately designed location-dependent density functions in in-homogeneous PPP models. However, the simultaneous existence of attractiveness and repulsiveness among BSs practically deployed in a large-scale area defies such an assumption, and the α-stable distribution, one kind of heavy-tailed distributions, has recently demonstrated superior accuracy to statistically model the varying BS density in different areas. In this paper, we start with these new findings and investigate the intrinsic feature (i.e., the spatial self-similarity) embedded in the BSs. Afterwards, we refer to a generalized PPP setup with α-stable distributed density and theoretically derive the related coverage probability. In particular, we give an upper bound of the derived coverage probability for high signal-to-interference-plus-noise ratio thresholds and show the monotonically decreasing property of this bound with respect to the variance of BS density. Besides, we prove that our model could reduce to the single-tier HPPP for some special cases and demonstrate the superior accuracy of the α-stable model to approach the real environment.

The traffic in the wireless networks has become diverse and fluctuating both spatially and temporally due to the emergence of new wireless applications. The purpose of this paper is to explore the impact of the wireless traffic with violent fluctuation both spatially and temporally on the performance of the wireless networks. We analyze the spatial statistics, the stability of queues and the delay of users by considering two different spatial distributions of traffic, i.e., the uniformly and non-uniformly distributed cases. The simulation results indicate that although the fluctuations of traffic when the users are clustered, reflected by the variance of total arrival rate, is much fiercer than that when the users are uniformly distributed, the stability performance is much better. Our work provides a useful reference for the design of the wireless networks when the complex spatio-temporal fluctuation of the traffic is considered.

Exchange of crucial and confidential information in wireless networks leads to the unprecedented attention on the security problem. Though a number of works have studied the physical layer security, the joint optimization of the end-to-end delay management and the physical layer security, which requires a meticulous cross-layer design, has seldom been evaluated in the literature. In this work, by combining the tools from queueing theory and stochastic geometry, we analyze the tradeoff between delay and physical layer security in large wireless networks. Our numerical results reveal that the security performance is better for larger path loss exponent when the density of legitimate nodes is large, and it is reverse when the density is small. Meanwhile, it is observed that under the condition that a certain confidential rate is guaranteed, the delay performance is better in high signal-to-interference ratio regime than that in low SIR regime. In summary, this work provides an understanding and a rule-of-thumb for the practical design of wireless networks where both the delay and the security are key concerns.

When small cells are densely deployed in the fifth‐generation cellular networks, switching off a part of base stations (BSs) is a practical approach for saving energy consumption considering the variation of traffic load. The small‐cell network with the massive multi‐input–multi‐output system is analysed in this study due to the dense deployment and low‐power consumption. On the basis ofn the BS‐switch‐off strategy with distance constraints, the energy and coverage efficiency are investigated to illustrate the performance of the BS‐switch‐off strategy. Simulation results indicate that the energy efficiency and coverage efficiency of the proposed strategy are better than the random strategy. The energy efficiency increases with the BS intensity and the minimal distance, and a maximum coverage efficiency can be achieved with the increase of the BS intensity and the minimum distance. In this case, the optimal BS‐switch‐off strategy can be designed under this work in the actual scene.

Exchange of crucial and confidential information leads to the unprecedented attention on the security problem in wireless networks. Even though the security has been studied in a number of works, the joint optimization of the physical layer security and the end-to-end delay management, which requires a meticulous cross-layer design, has seldom been evaluated. In this paper, by combining the tools from stochastic geometry and queueing theory, we analyze the tradeoff between the delay and the security performance in large wireless networks. We further propose a simple transmission mechanism which splits a message into two packets and evaluate its effect on the mean delay and the secrecy outage probability. Our numerical results reveal that the security performance is better for larger path loss exponent when the density of legitimate nodes is large, and it is reverse when the density is small. Moreover, it is observed that by introducing the simple mechanism of message split, the security performance is greatly improved in the backlogged scenario and slightly improved in the dynamic scenario when the density of legitimate transmitters is large. In summary, this paper provides an understanding and a rule-of-thumb for the practical design of wireless networks where both the delay and the security are key concerns.

In this paper, we develop a framework using tools from stochastic geometry and queuing theory to evaluate the flow-level performance of downlink cellular networks with spatio-temporal traffic. Under this framework, we first obtain the mean service rate and the non-empty probability of a scheduled user queue by solving a fixed-point equation, which captures the inherent correlation between the interference and the queue status. By leveraging these results, we then derive closed-form expressions for the mean packet throughput and its bounds, defined as the mean number of packets that can be delivered during a given time duration. Simulation results validate the accuracy of the presented analysis, which can provide useful insight on the design of cellular networks while incorporating the spatial and temporal fluctuations of traffic.

Full-duplex (FD) allows the exchange of data between nodes on the same temporal and spectrum resources, however, it introduces self interference (SI) and additional network interference compared to half-duplex (HD). Power control in the FD networks, which is seldom studied in the literature, is promising to mitigate the interference and improve the performance of the overall network. In this work, we investigate the random and deterministic power control strategies in the FD networks, namely, constant power control, uniform power control, fractional power control and ALOHA-like random on-off power control scheme. Based on the obtained coverage probabilities and their robust approximations, we show that power control provides remarkable gain in area spectrum efficiency (ASE) and energy efficiency (EE), and improves the fairness among the uplink (UL) and downlink (DL) transmissions with respect to the FD networks. Moreover, we evaluate the minimum SI cancellation capability to guarantee the performance of the cell-edge users in FD networks. Generally, power control is helpful to improve the performance of the transmission for long distance in the FD networks and reduce the requirement of SI cancellation capability.

Emergence of new types of services has led to various traffic and diverse delay requirements in fifth-generation (5G) wireless networks. Meeting diverse delay requirements is one of the most critical goals for the design of 5G wireless networks. Though the delay of point-to-point communications has been well investigated, the delay of multi-point to multi-point communications has not been thoroughly studied, since it is a complicated function of all links in the network. In this paper, we propose a novel tractable approach to analyze the delay in the heterogeneous cellular networks with spatio-temporal random arrival of traffic. Specifically, we propose the notion of delay outage and evaluate the effect of different scheduling policies on the delay performance. Our numerical analysis reveals that offloading policy based on the cell range expansion greatly reduces the macrocell traffic, while bringing a small amount of growth for the picocell traffic. Our results also show that the delay performance of round-robin scheduling outperforms first-in first-out scheduling for heavy traffic, and it is reversed for light traffic. In summary, this analytical framework provides an understanding and a rule-of-thumb for the practical deployment of 5G systems, where delay requirement is increasingly becoming a key concern.

Cloud radio access networks (C-RANs) architecture is a cost-efficient and energy-efficient solution for increasing the capacity of the cellular network. In order to adapt the traffic and reduce the system cost, we propose complementary networking architecture for the C-RAN, which takes advantage of both the C-RAN and traditional base stations (BSs). We propose combining the Neyman-Scott cluster process and the Poisson hole process to model the architecture; then, the interference in the large-scale network with cooperation is well characterized through the Poisson point process approximation. By mixing the two multiple association mechanisms, i.e., the RRH-selection mode and the cooperation mode, we explore the tradeoffs between the area spectrum efficiency (ASE), the mean delay, and the system cost both analytically and numerically. The results reveal that the mean delay is negative correlated to the ASE for small ASE and is reversed for large ASE, while the cost is always positively correlated to the ASE. The cooperation mode increases the useful signal as well as the interference, which becomes dominant when the radius of the RRH cluster is large. The proportion of sub-frames operating in the two modes can be configured to tradeoff the ASE, the mean delay, and the cost.

Gauss-Poisson processes (GPPs) are a class of clustered point processes, which include the Poisson point process as a special case and have a simpler structure than the general Poisson cluster point processes. A key property of the GPP is that it is completely defined by its first- and second-order statistics. In this paper, we first show the properties of the GPP and provide an approach to fit the GPP to a given point set. A fitting example is presented. We then propose the GPP as a model for wireless networks that exhibit clustering behavior and derive the signal-to-interference-ratio distributions for different system models: 1) the basic model where the desired transmitter is independent of the GPP and all nodes in the GPP are interferers; 2) the non-cooperative model where the desired transmitter is one of the nodes in the GPP; and 3) the cooperative model, where the nodes in a GPP cluster transmit cooperatively. The simulation results indicate that a significant gain can be achieved with cooperation.

We investigate the stable packet arrival rate region of a discrete-time slotted random access network, where the sources are distributed as a Poisson point process. Each of the sources in the network has a destination at a given distance and a buffer of infinite capacity. The network is assumed to be random but static, i.e., the sources and the destinations are placed randomly and remain static during all the time slots. We employ tools from queueing theory as well as point process theory to study the stability of this system using the concept of dominance. The problem is an instance of the interacting queues problem, further complicated by the Poisson spatial distribution. We obtain sufficient conditions and necessary conditions for stability. Numerical results show that the gap between the sufficient conditions and the necessary conditions is small when the access probability, the density of transmitters, or the SINR threshold is small. The results also reveal that a slight change of the arrival rate may greatly affect the fraction of unstable queues in the network.

Heterogeneous cellular networks (HetNets) are to be deployed for future wireless communication to meet the ever-increasing mobile traffic demand. However, the dense and random deployment of small cells and their uncoordinated operation raise important concerns about energy efficiency. On the other hand, discontinuous transmission (DTX) mode at the base station (BS) serves as an effective technology to improve the energy efficiency of overall system. In this paper, we investigate the energy efficiency under the finite local delay constraint in the downlink HetNets with random DTX scheme. Using a stochastic geometry based model, we derive the local delay and energy efficiency in the general case and obtain closed-form expressions in some special cases. These results give some useful insights on the system performance, taking the tradeoff between local delay and energy efficiency into account. Furthermore, we provide the low-rate and high-rate asymptotic behavior of the maximum energy efficiency. It is analytically shown that it is less energy-efficient to apply random DTX scheme in the low-rate regime. However, in the high-rate regime, random DTX scheme is essential to achieve the finite local delay and higher energy efficiency.

Dynamic TDD is promising to improve the performance of cellular networks since the UL and DL configurations could be modified to match the instantaneous traffic. However, for the neighbor cells of opposite transmission directions, the base station-to-base station interference from the DL cell greatly limits the performance of UL cell. In this work, we first provide a detailed model that abstracts the practical system and analyze the interference of the network by leveraging tools from point process theory. Then, based on the conclusions from theoretical analysis, we propose several distributed interference coordination schemes to mitigate the interference for dynamic TDD. Simulation results show that subframe-dependent OI with interference source is effective to improve the performance of the network, and that interference type information does not help much for subframe-dependent OI while eNB-eNB measurement can efficiently improve the performance of subframe-specific OI.

The stable packet arrival rate region of the discrete-time slotted ALOHA network with the sources distributed as a static Poisson point process is investigated here. The problem is a generalization and extension of interacting queues problem, in which the physical layer is abstracted. Employing tools from queueing theory as well as point process theory, we obtain sufficient conditions and necessary conditions for stability by the concept of dominance. Numerical results show that the gap between sufficient conditions and necessary conditions is small, and the results also reveal how these conditions vary with system parameters.

Transmission of layered source information, such as scalable video coding (SVC), over heterogenous wireless networks is considered in this work. Scalable transmission enables dynamic adaption of source information to the condition of user equipments, and thus is suitable for heterogenous networks in which the transmission link quality varies substantially. Leveraging tools in stochastic geometry, a comprehensive analysis is conducted for several different transmission protocols, focusing on two key performance metrics, Standard-Definition outage probability and High-Definition probability. The proposed transmission protocols are compared in different aspects, and the benefit of interference cancellation is shown to be significant.

The RTS/CTS handshake mechanism in WLAN is studied using stochastic geometry. The effect of RTS/CTS is treated as a thinning procedure for a spatially point process that models the potential transceivers in a WLAN, and the resulting concurrent transmitter processes are described. Exact formulas for the intensity of the concurrent transmitter processes and the mean interference are established. The analysis yields useful results for understanding how the design parameters of RTS/CTS affect the interference in the network.

Gauss-Poisson processes (GPPs) are a class of clustered point processes, which include the Poisson point process as a special case and have a simpler structure than general Poisson cluster point processes. In this paper, we propose the GPP as a model for wireless networks that exhibit clustering behavior. We calculate the success probabilities and provide bounds for three kinds of GPP networks: (1) the basic model where the desired transmitter is independent of the GPP and all nodes in the GPP are interferers; (2) the non-cooperative model where the desired transmitter is one of the nodes in the GPP; (3) the cooperative model where both nodes in a two-node cluster of the GPP serve a receiver cooperatively using non-coherent joint transmission. Our results show that the bounds, especially the upper bounds, provide good approximations for different operating regimes.

Modeling the spatial distribution of multi-tier base stations (BSs) is an important issue for understanding and validating the analysis and design of heterogeneous cellular networks (HCNs). In this paper, we use different spatial statistical models to describe the spatial distribution of BSs, by fitting real data sets of BS locations in HCNs. Classical statistics like the L function, and cellular network performance metrics like the coverage probability are used to evaluate the goodness-of-fit. The results reveal that notable distinctions exist between modeling HCNs and single-tier networks. Although each tier in a HCN may be most accurately fitted by statistical models other than the Poisson spatial distribution, it is surprising that multiple tiers of independent Poisson spatial distributions provide an accurate description of the overall HCN. The impacts of different network parameters and the dependency between tiers on the modeling accuracy are extensively investigated.

The capacity of wireless networks is fundamentally limited by interference. However, little research has focused on the interference correlation, which may greatly increase the local delay (namely the number of time slots required for a node to successfully transmit a packet). This paper focuses on the question whether increasing randomness in the MAC, specifically frequency-hopping multiple access (FHMA) and ALOHA, helps to reduce the effect of interference correlation. We derive closed-form results for the mean and variance of the local delay for the two MAC protocols and evaluate the optimal parameters that minimize the mean local delay. Based on the optimal parameters, we identify two operating regimes, the correlation-limited regime and the bandwidth-limited regime. Our results reveal that while the mean local delays for FHMA with N sub-bands and for ALOHA with transmit probability p essentially coincide when p=1/N, a fundamental discrepancy exists between their variances. We also discuss implications from the analysis, including an interesting mean delay-jitter tradeoff, and convenient bounds on the tail probability of the local delay, which shed useful insights into system design.

For two-tier networks consisting of macrocells and femtocells, the channel access mechanism can be configured to be open access, closed access, or hybrid access. Hybrid access arises as a compromise between open and closed access mechanisms, in which a fraction of available spectrum resource is shared to nonsubscribers while the remaining reserved for subscribers. This paper focuses on a hybrid access mechanism for multi-channel femtocells which employ orthogonal spectrum access schemes. Considering a randomized channel assignment strategy, we analyze the performance in the downlink. Using stochastic geometry as technical tools, we model the distribution of femtocells as Poisson point process or Neyman-Scott cluster process and derive the distributions of signal-to-interference-plus-noise ratios, and mean achievable rates, of both nonsubscribers and subscribers. The established expressions are amenable to numerical evaluation, and shed key insights into the performance tradeoff between subscribers and nonsubscribers. The analytical results are corroborated by numerical simulations.

For two-tier networks consisting of macrocells and femtocells, the channel access mechanism can be configured to be open access, closed access, or hybrid access. Hybrid access arises as a compromise between open and closed access mechanisms, in which a fraction of available spectrum resource is shared to nonsubscribers while the remaining reserved for subscribers. This paper focuses on a hybrid access mechanism for multi-channel femtocells which employ orthogonal spectrum access schemes. Considering a randomized channel assignment strategy, we analyze the performance in the downlink. Using stochastic geometry as technical tools, we derive the distributions of signal-to-interference-plus-noise ratios, and mean achievable rates, of both nonsubscribers and subscribers. The established expressions are amenable to numerical evaluation, and shed key insights into the performance tradeoff between subscribers and nonsubscribers. The analytical results are corroborated by numerical simulations.