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Multi-agent Deep Reinforcement Learning (MADRL) based traffic signal control becomes a popular research topic in recent years. To alleviate the scalability issue of completely centralized RL techniques and the non-stationarity issue of completely decentralized RL techniques on large-scale traffic networks, some literature utilizes a regional control approach where the whole network is firstly partitioned into multiple disjoint regions, followed by applying the centralized RL approach to each region. However, the existing partitioning rules either have no constraints on the topology of regions or require the same topology for all regions. Meanwhile, no existing regional control approach explores the performance of optimal joint action in an exponentially growing regional action space when intersections are controlled by 4-phase traffic signals (EW, EWL, NS, NSL). In this paper, we propose a novel RL training framework named RegionLight to tackle the above limitations. Specifically, the topology of regions is firstly constrained to a star network which comprises one center and an arbitrary number of leaves. Next, the network partitioning problem is modeled as an optimization problem to minimize the number of regions. Then, an Adaptive Branching Dueling Q-Network (ABDQ) model is proposed to decompose the regional control task into several joint signal control sub-tasks corresponding to particular intersections. Subsequently, these sub-tasks maximize the regional benefits cooperatively. Finally, the global control strategy for the whole network is obtained by concatenating the optimal joint actions of all regions. Experimental results demonstrate the superiority of our proposed framework over all baselines under both real and synthetic datasets in all evaluation metrics.

While the increased automation levels of production and operation equipment have led to improved productivity of mining activity in open pit mines, the capacity of mine transport system become a bottleneck. The optimization of mine transport system is of great practical significance to reduce the production and operation cost and improve the production and organizational efficiency of mines. In this paper we first formulate a multi-objective optimisation problem for mine railway scheduling by introducing a set of mathematical constraints. As the problem is NP-hard, we then devise a Mixed Integer Programming based solution to solve this problem, and develop an online framework accordingly. We finally conduct test cases to evaluate the performance of the proposed solution. Experimental results demonstrate that the proposed solution is efficient and able to generate train schedule in a real-time manner.

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions., Comment: The current version has partial Insufficient completion, so we would like to withdraw it. We hope you agree, thank you

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., Comment: IEEE Journal on Selected Areas in Communications, accepted to appear

Channel estimation (CE) for millimeter-wave (mmWave) lens-array suffers from prohibitive training overhead, whereas the state-of-the-art solutions require an extra complicated radio frequency phase shift network. By contrast, lens-array using antenna switching network (ASN) simplifies the hardware, but the associated CE is a challenging task due to the constraint imposed by ASN. This paper proposes a compressive sensing (CS)-based CE solution for full-dimensional (FD) lens-array, where the mmWave channel sparsity is exploited. Specifically, we first propose an approach of pilot training under the more severe haraware constraint imposed by ASN, and formulate the associated CE of lens-array as a CS problem. Then, a redundant dictionary is tailored for FD lens-array to combat the power leakage caused by the continuous angles of multipath components. Further, we design the baseband pilot signals to minimize the total mutual coherence of the measurement matrix based on CS theory for more reliable CE performance. Our solution provides a framework for applying CS techniques to lens-array using simple and practical ASN. Simulation results demonstrate the effectiveness of the proposed scheme., Comment: 6 pages, 6 figures, accepted by IEEE Transactions on Vehicular Technology

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, multi-hop transmissions will become an important transmission mechanism in IoT networks. It is crucial for lowpower devices to transmit data over long distances via multihop in a low-delay and reliable way. 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 paper, 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 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). 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., Comment: 12 pages,11 figures,journal

Hybrid analog-digital precoding is challenging for broadband millimeter-wave (mmWave) massive MIMO systems, since the analog precoder is frequency-flat but the mmWave channels are frequency-selective. In this paper, we propose a principal component analysis (PCA)-based broadband hybrid precoder/combiner design, where both the fully-connected array and partially-connected subarray (including the fixed and adaptive subarrays) are investigated. Specifically, we first design the hybrid precoder/combiner for fully-connected array and fixed subarray based on PCA, whereby a low-dimensional frequency-flat precoder/combiner is acquired based on the optimal high-dimensional frequency-selective precoder/combiner. Meanwhile, the near-optimality of our proposed PCA approach is theoretically proven. Moreover, for the adaptive subarray, a low-complexity shared agglomerative hierarchical clustering algorithm is proposed to group the antennas for the further improvement of spectral efficiency (SE) performance. Besides, we theoretically prove that the proposed antenna grouping algorithm is only determined by the slow time-varying channel parameters in the large antenna limit. Simulation results demonstrate the superiority of the proposed solution over state-of-the-art schemes in SE, energy efficiency (EE), bit-error-rate performance, and the robustness to time-varying channels. Our work reveals that the EE advantage of adaptive subarray over fully-connected array is obvious for both active and passive antennas, but the EE advantage of fixed subarray only holds for passive antennas., Comment: to be published in IEEE Transactions on Wireless Communications

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., Comment: accepted in Transactions on Communications

Secure message dissemination is an important issue in vehicular networks, especially considering the vulnerability of vehicle to vehicle message dissemination to malicious attacks. Traditional security mechanisms, largely based on message encryption and key management, can only guarantee secure message exchanges between known source and destination pairs. In vehicular networks however, every vehicle may learn its surrounding environment and contributes as a source, while in the meantime act as a destination or a relay of information from other vehicles, message exchanges often occur between "stranger" vehicles. For secure message dissemination in vehicular networks against insider attackers, who may tamper the content of the disseminated messages, ensuring the consistency and integrity of the transmitted messages becomes a major concern that traditional message encryption and key management based approaches fall short to provide. In this paper, by incorporating the underlying network topology information, we propose an optimal decision algorithm that is able to maximize the chance of making a correct decision on the message content, assuming the prior knowledge of the percentage of malicious vehicles in the network. Furthermore, a novel heuristic decision algorithm is proposed that can make decisions without the aforementioned knowledge of the percentage of malicious vehicles. Simulations are conducted to compare the security performance achieved by our proposed decision algorithms with that achieved by existing ones that do not consider or only partially consider the topological information, to verify the effectiveness of the algorithms. Our results show that by incorporating the network topology information, the security performance can be much improved. This work shed light on the optimum algorithm design for secure message dissemination.

From very recent studies, the area spectral efficiency (ASE) performance of downlink (DL) cellular networks will continuously decrease and finally to zero with the network densification in a fully loaded ultra-dense network (UDN) when the absolute height difference between a base station (BS) antenna and a user equipment (UE) antenna is larger than zero, which is referred as the ASE Crash. We revisit this issue by considering the impact of the BS antenna downtilt on the downlink network capacity. In general, there exists a height difference between a BS and a UE in practical networks. It is common to utilize antenna downtilt to adjust the direction of the vertical antenna pattern, and thus increase received signal power or reduce inter-cell interference power to improve network performance. This paper focuses on investigating the relationship between the base station antenna downtilt and the downlink network capacity in terms of the coverage probability and the ASE. The analytical results of the coverage probability and the ASE are derived, and we find that there exists an optimal antenna downtilt to achieve the maximal coverage probability for each base station density. Moreover, we derive numerically solvable expressions for the optimal antenna downtilt, which is a function of the base station density. Our theoretical and numerical results show that after applying the optimal antenna downtilt, the network performance can be improved significantly. Specifically, with the optimal antenna downtilt, the ASE crash can be delayed by nearly one order of magnitude in terms of the base station density.

We investigate network performance of ultra-dense heterogeneous networks (HetNets) and study the maximum energy-efficient base station (BS) deployment incorporating probabilistic non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions. First, we develop an analytical framework with the maximum instantaneous received power (MIRP) and the maximum average received power (MARP) association schemes to model the coverage probability and related performance metrics, e.g., the potential throughput (PT) and the energy efficiency (EE). Second, we formulate two optimization problems to achieve the maximum energy-efficient deployment solution with specific service criteria. Simulation results show that there are tradeoffs among the coverage probability, the total power consumption, and the EE. To be specific, the maximum coverage probability with ideal power consumption is superior to that with practical power consumption when the total power constraint is small and inferior to that with practical power consumption when the total power constraint becomes large. Moreover, the maximum EE is a decreasing function with respect to the coverage probability constraint., Comment: Submitted to IEEE Transactions on Green Communications and Networking

User distribution in ultra-dense networks (UDNs) plays a crucial role in affecting the performance of UDNs due to the essential coupling between the traffic and the service provided by the networks. Existing studies are mostly based on the assumption that users are uniformly distributed in space. The non-uniform user distribution has not been widely considered despite that it is much closer to the real scenario. In this paper, Radiation and Absorbing model (R&A model) is first adopted to analyze the impact of the non-uniformly distributed users on the performance of 5G UDNs. Based on the R&A model and queueing network theory, the stationary user density in each hot area is investigated. Furthermore, the coverage probability, network throughput and energy efficiency are derived based on the proposed theoretical model. Compared with the uniformly distributed assumption, it is shown that non-uniform user distribution has a significant impact on the performance of UDNs., Comment: 14 pages, 10 figures

Augmented and/or virtual reality (AR/VR) are emerging as one of the main applications in future fifth generation (5G) networks. To meet the requirements of lower latency and massive data transmission in AR/VR applications, a solution with software-defined networking (SDN) architecture is proposed for 5G small cell networks. On this basis, a multi-path cooperative route (MCR) scheme is proposed to facilitate the AR/VR wireless transmissions in 5G small cell networks, in which the delay of MCR scheme is analytically studied. Furthermore, a service effective energy optimal (SEEO) algorithm is developed for AR/VR wireless transmission in 5G small cell networks. Simulation results indicate that both the delay and service effective energy (SEE) of the proposed MCR scheme outperform the delay and SEE of the conventional single path route scheme in 5G small cell networks., Comment: 30 pages, 10 figures

In this paper, we answer a fundamental question: when the total number of antennas per square kilometer is fixed, what is the optimal network deployment? A denser network with a less number of antennas per base station (BS) or the opposite case. To evaluate network performance, we consider a practical network scenario with a fixed antennas density and multiuser multiple-input-multiple-output (MU-MIMO) operations for single-antenna users. The number of antennas in each BS is calculated by dividing the antenna density by the BS density. With the consideration of several practical network models, i.e., pilot contamination, a limited user equipment (UE) density and probabilistic line-of-sight (LoS)/non-line-of-sight (NLoS) path loss model, we evaluate the area spectral efficiency (ASE) performance. From our simulation results, we conclude that there exists an optimal BS density for a certain UE density to maximize the ASE performance when the antenna density is fixed. The intuition is that (i) by densifying the network with more BSs, we can achieve a receive power gain due to the smaller distance between the typical UE and its serving BS; (ii) by installing more antennas in each BS, we can achieve a beamforming gain for UEs using MU-MIMO, although such beamforming gain is degraded by pilot contamination; (iii) thus, a trade-off exists between the receive power gain and the beamforming gain, if we fix the antenna density in the network., Comment: to appear in Globecom 2017

For device-to-device (D2D) communications underlaying a cellular network with uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we address the critical issue of interference management in the network considering a practical path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. To reduce the severe interference caused by active D2D links, we consider a mode selection scheme based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Specifically, a UE will operate in a cellular mode, only if its received signal strength from the strongest base station (BS) is larger than a threshold beta; otherwise, the UE will operate in a D2D mode. Furthermore, we analyze the performance in terms of the coverage probability and the area spectral efficiency (ASE) for both the cellular network and the D2D one. Analytical results are obtained and the accuracy of the proposed analytical framework is validated through Monte Carol simulations. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications in cellular networks and we find an optimum mode selection threshold beta to maximize the total ASE in the network.

In this paper, we theoretically study the proportional fair (PF) scheduler in the context of ultra-dense networks (UDNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE) performance of dense small cell networks (SCNs) with the PF scheduler employed at base stations (BSs). The key point of our analysis is that the typical user is no longer a random user as assumed in most studies in the literature. Instead, a user with the maximum PF metric is chosen by its serving BS as the typical user. By comparing the previous results of the round-robin (RR) scheduler with our new results of the PF scheduler, we quantify the loss of the multi-user diversity of the PF scheduler with the network densification, which casts a new look at the role of the PF scheduler in UDNs. Our conclusion is that the RR scheduler should be used in UDNs to simplify the radio resource management (RRM)., Comment: To appear in IEEE GLOBECOM2017

This paper studies the impact of the base station (BS) idle mode capability (IMC) on the network performance of multi-tier and dense heterogeneous cellular networks (HCNs). Different from most existing works that investigated network scenarios with an infinite number of user equipments (UEs), we consider a more practical setup with a finite number of UEs in our analysis. More specifically, we derive the probability of which BS tier a typical UE should associate to and the expression of the activated BS density in each tier. Based on such results, analytical expressions for the coverage probability and the area spectral efficiency (ASE) in each tier are also obtained. The impact of the IMC on the performance of all BS tiers is shown to be significant. In particular, there will be a surplus of BSs when the BS density in each tier exceeds the UE density, and the overall coverage probability as well as the ASE continuously increase when the BS IMC is applied. Such finding is distinctively different from that in existing work. Thus, our result sheds new light on the design and deployment of the future 5G HCNs., Comment: conference submission

In this paper, using the stochastic geometry theory, we present a framework for analyzing the performance of device-to-device (D2D) communications underlaid uplink (UL) cellular networks. In our analysis, we consider a D2D mode selection criterion based on an energy threshold for each user equipment (UE). Specifically, a UE will operate in a cellular mode, if its received signal strength from the strongest base station (BS) is large than a threshold \beta. Otherwise, it will operate in a D2D mode. Furthermore, we consider a generalized log-normal shadowing in our analysis. The coverage probability and the area spectral efficiency (ASE) are derived for both the cellular network and the D2D one. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and provide guidelines of selecting the parameters for network operations., Comment: conference submission

The aggressive spatial spectrum reuse (SSR) by network densification using smaller cells has successfully driven the wireless communication industry onward in the past decades. In our future journey toward ultra-dense networks (UDNs), a fundamental question needs to be answered. Is there a limit to SSR? In other words, when we deploy thousands or millions of small cell base stations (BSs) per square kilometer, is activating all BSs on the same time/frequency resource the best strategy? In this paper, we present theoretical analyses to answer such question. In particular, we find that both the signal and interference powers become bounded in practical UDNs with a non-zero BS-to-UE antenna height difference and a finite UE density, which leads to a constant capacity scaling law. As a result, there exists an optimal SSR density that can maximize the network capacity. Hence, the limit to SSR should be considered in the operation of future UDNs., Comment: conference submission in Oct. 2017

Information security is an important issue in vehicular networks as the accuracy and integrity of information is a prerequisite to satisfactory performance of almost all vehicular network applications. In this paper, we study the information security of a vehicular ad hoc network whose message may be tampered by malicious vehicles. An analytical framework is developed to analyze the process of message dissemination in a vehicular network with malicious vehicles randomly distributed in the network. The probability that a destination vehicle at a fixed distance away can receive the message correctly from the source vehicle is obtained. Simulations are conducted to validate the accuracy of the theoretical analysis. Our results demonstrate the impact of network topology and the distribution of malicious vehicles on the correct delivery of a message in vehicular ad hoc networks, and may provide insight on the design of security mechanisms to improve the security of message dissemination in vehicular networks.

In this paper, we propose a unified framework to analyze the performance of dense small cell networks (SCNs) in terms of the coverage probability and the area spectral efficiency (ASE). In our analysis, we consider a practical path loss model that accounts for both non-line-of-sight (NLOS) and line-of-sight (LOS) transmissions. Furthermore, we adopt a generalized fading model, in which Rayleigh fading, Rician fading and Nakagami-m fading can be treated in a unified framework. The analytical results of the coverage probability and the ASE are derived, using a generalized stochastic geometry analysis. Different from existing work that does not differentiate NLOS and LOS transmissions, our results show that NLOS and LOS transmissions have a significant impact on the coverage probability and the ASE performance, particularly when the SCNs grow dense. Furthermore, our results establish for the first time that the performance of the SCNs can be divided into four regimes, according to the intensity (aka density) of BSs, where in each regime the performance is dominated by different factors., Comment: 3 figures. Accepted by ICC 2017

Multi-agent systems (MAS) is able to characterize the behavior of individual agent and the interaction between agents. Thus, it motivates us to leverage the distributed constraint optimization problem (DCOP), a framework of modeling MAS, to solve the user association problem in heterogeneous networks (HetNets). Two issues we have to consider when we take DCOP into the application of HetNet including: (i) How to set up an effective model by DCOP taking account of the negtive impact of the increment of users on the modeling process (ii) Which kind of algorithms is more suitable to balance the time consumption and the quality of soltuion. Aiming to overcome these issues, we firstly come up with an ECAV-$\eta$ (Each Connection As Variable) model in which a parameter $\eta$ with an adequate assignment ($\eta=3$ in this paper) is able to control the scale of the model. After that, a Markov chain (MC) based algorithm is proposed on the basis of log-sum-exp function. Experimental results show that the solution obtained by DCOP framework is better than the one obtained by the Max-SINR algorithm. Comparing with the Lagrange dual decomposition based method (LDD), the solution performance has been improved since there is no need to transform original problem into a satisfied one. In addition, it is also apparent that the DCOP based method has better robustness than LDD when the number of users increases but the available resource at base stations are limited.

Considering both non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions, the transitional behaviors from noise-limited regime to dense interference-limited regime have been investigated for the fifth generation (5G) small cell networks (SCNs). Besides, we identify four performance regimes based on base station (BS) density, i.e., (i) the noise-limited regime, (ii) the signal-dominated regime, (iii) the interference-dominated regime, and (iv) the interference-limited regime. To characterize the performance regime, we propose a unified framework analyzing the future 5G wireless networks over generalized shadowing/fading channels, in which the user association schemes based on the strongest instantaneous received power (SIRP) and the strongest average received power (SARP) can be studied, while NLoS/LoS transmissions and multi-slop path loss model are considered. Simulation results indicate that different factors, i.e., noise, desired signal, and interference, successively and separately dominate the network performance with the increase of BS density. Hence, our results shed new light on the design and management of SCNs in urban and rural areas with different BS deployment densities., Comment: 15 pages, double-columned, 8 figures. Rejected by IEEE Transactions on Communications and accepted by IEEE Transactions on Vehicular Technology

Based on the observation that the correlation between observed traffic at two measurement points or traffic stations may be time-varying, attributable to the time-varying speed which subsequently causes variations in the time required to travel between the two points, in this paper, we develop a modified Space-Time Autoregressive Integrated Moving Average (STARIMA) model with time-varying lags for short-term traffic flow prediction. Particularly, the temporal lags in the modified STARIMA change with the time-varying speed at different time of the day or equivalently change with the (time-varying) time required to travel between two measurement points. Firstly, a technique is developed to evaluate the temporal lag in the STARIMA model, where the temporal lag is formulated as a function of the spatial lag (spatial distance) and the average speed. Secondly, an unsupervised classification algorithm based on ISODATA algorithm is designed to classify different time periods of the day according to the variation of the speed. The classification helps to determine the appropriate time lag to use in the STARIMA model. Finally, a STARIMA-based model with time-varying lags is developed for short-term traffic prediction. Experimental results using real traffic data show that the developed STARIMA-based model with time-varying lags has superior accuracy compared with its counterpart developed using the traditional cross-correlation function and without employing time-varying lags.

Cooperative geolocation has attracted significant research interests in recent years. A large number of localization algorithms rely on the availability of statistical knowledge of measurement errors, which is often difficult to obtain in practice. Compared with the statistical knowledge of measurement errors, it can often be easier to obtain the measurement error bound. This work investigates a localization problem assuming unknown measurement error distribution except for a bound on the error. We first formulate this localization problem as an optimization problem to minimize the worst-case estimation error, which is shown to be a non-convex optimization problem. Then, relaxation is applied to transform it into a convex one. Furthermore, we propose a distributed algorithm to solve the problem, which will converge in a few iterations. Simulation results show that the proposed algorithms are more robust to large measurement errors than existing algorithms in the literature. Geometrical analysis providing additional insights is also provided.

This paper investigates the use of WiFi and mobile device-to-device networks, with vehicular ad hoc networks being a typical example, as a complementary means to offload and reduce the traffic load of cellular networks. A novel cooperative content dissemination strategy is proposed for a heterogeneous network consisting of different types of devices with different levels of mobility, ranging from static WiFi access points to mobile devices such as vehicles. The proposed strategy offloads a significant proportion of data traffic from cellular networks to WiFi or device-to-device networks. Detailed analysis is provided for the content dissemination process in heterogeneous networks adopting the strategy. On that basis, the optimal parameter settings for the content dissemination strategy are discussed. Simulation and numerical studies show that the proposed strategy effectively reduces data traffic for cellular networks while guaranteeing successful content delivery., Comment: three figures, published in the 19th IEEE Intelligent Transportation Systems Conference

In this paper, we focus on one of the representative 5G network scenarios, namely multi-tier heterogeneous cellular networks. User association is investigated in order to reduce the down-link co-channel interference. Firstly, in order to analyze the multi-tier heterogeneous cellular networks where the base stations in different tiers usually adopt different transmission powers, we propose a Transmission Power Normalization Model (TPNM), which is able to convert a multi-tier cellular network into a single-tier network, such that all base stations have the same normalized transmission power. Then using TPNM, the signal and interference received at any point in the complex multi-tier environment can be analyzed by considering the same point in the equivalent single-tier cellular network model, thus significantly simplifying the analysis. On this basis, we propose a new user association scheme in heterogeneous cellular networks, where the base station that leads to the smallest interference to other co-channel mobile stations is chosen from a set of candidate base stations that satisfy the quality-of-service (QoS) constraint for an intended mobile station. Numerical results show that the proposed user association scheme is able to significantly reduce the down-link interference compared with existing schemes while maintaining a reasonably good QoS., Comment: 7 pages, 3 figures

The wireless backhaul network provides an attractive solution for the urban deployment of fifth generation (5G) wireless networks that enables future ultra dense small cell networks to meet the ever-increasing user demands. Optimal deployment and management of 5G wireless backhaul networks is an interesting and challenging issue. In this paper we propose the optimal gateways deployment and wireless backhaul route schemes to maximize the cost efficiency of 5G wireless backhaul networks. In generally, the changes of gateways deployment and wireless backhaul route are presented in different time scales. Specifically, the number and locations of gateways are optimized in the long time scale of 5G wireless backhaul networks. The wireless backhaul routings are optimized in the short time scale of 5G wireless backhaul networks considering the time-variant over wireless channels. Numerical results show the gateways and wireless backhaul route optimization significantly increases the cost efficiency of 5G wireless backhaul networks. Moreover, the cost efficiency of proposed optimization algorithm is better than that of conventional and most widely used shortest path (SP) and Bellman-Ford (BF) algorithms in 5G wireless backhaul networks.

Capacity of vehicular networks with infrastructure support is both an interesting and challenging problem as the capacity is determined by the inter-play of multiple factors including vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, density and mobility of vehicles, and cooperation among vehicles and infrastructure. In this paper, we consider a typical delay-tolerant application scenario with a subset of vehicles, termed Vehicles of Interest (VoIs), having download requests. Each VoI downloads a distinct large-size file from the Internet and other vehicles without download requests assist the delivery of the files to the VoIs. A cooperative communication strategy is proposed that explores the combined use of V2I communications, V2V communications, mobility of vehicles and cooperation among vehicles and infrastructure to improve the capacity of vehicular networks. An analytical framework is developed to model the data dissemination process using this strategy, and a closed form expression of the achievable capacity is obtained, which reveals the relationship between the capacity and its major performance-impacting parameters such as inter-infrastructure distance, radio ranges of infrastructure and vehicles, sensing range of vehicles, transmission rates of V2I and V2V communications, vehicular density and proportion of VoIs. Numerical result shows that the proposed cooperative communication strategy significantly boosts the capacity of vehicular networks, especially when the proportion of VoIs is low. Our results provide guidance on the optimum deployment of vehicular network infrastructure and the design of cooperative communication strategy to maximize the capacity.

In this paper, we provide detailed analysis of the achievable throughput of infrastructure-based vehicular network with a finite traffic density under a cooperative communication strategy, which explores combined use of vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, mobility of vehicles and cooperations among vehicles and infrastructure to facilitate the data transmission. A closed form expression of the achievable throughput is obtained, which reveals the relationship between the achievable throughput and its major performance-impacting parameters such as distance between adjacent infrastructure points, radio ranges of infrastructure and vehicles, transmission rates of V2I and V2V communications and vehicular density. Numerical and simulation results show that the proposed cooperative communication strategy significantly increases the throughput of vehicular networks, compared with its non-cooperative counterpart, even when the traffic density is low. Our results shed insight on the optimum deployment of vehicular network infrastructure and optimum design of cooperative communication strategies in vehicular networks to maximize the throughput.

Small cell networks (SCNs) are envisioned to embrace dynamic time division duplexing (TDD) in order to tailor downlink (DL)/uplink (UL) subframe resources to quick variations and burstiness of DL/UL traffic. The study of dynamic TDD is particularly important because it provides valuable insights on the full duplex transmission technology, which has been identified as one of the candidate technologies for the 5th-generation (5G) networks. Up to now, the existing works on dynamic TDD have shown that the UL of dynamic TDD suffers from severe performance degradation due to the strong DL-to-UL interference in the physical (PHY) layer. This conclusion raises a fundamental question: Despite such obvious technology disadvantage, what is the true value of dynamic TDD? In this paper, we answer this question from a media access control (MAC) layer viewpoint and present analytical results on the DL/UL time resource utilization (TRU) of synchronous dynamic TDD, which has been widely adopted in the existing 4th-generation (4G) systems. Our analytical results shed new light on the dynamic TDD in future synchronous 5G networks., Comment: To appear in IEEE GLOBECOM2017

In this paper, we analyse the coverage probability and the area spectral efficiency (ASE) for the uplink (UL) of dense small cell networks (SCNs) considering a practical path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. Compared with the existing work, we adopt the following novel approaches in our study: (i) we assume a practical user association strategy (UAS) based on the smallest path loss, or equivalently the strongest received signal strength; (ii) we model the positions of both base stations (BSs) and the user equipments (UEs) as two independent Homogeneous Poisson point processes (HPPPs); and (iii) the correlation of BSs' and UEs' positions is considered, thus making our analytical results more accurate. The performance impact of LoS and NLoS transmissions on the ASE for the UL of dense SCNs is shown to be significant, both quantitatively and qualitatively, compared with existing work that does not differentiate LoS and NLoS transmissions. In particular, existing work predicted that a larger UL power compensation factor would always result in a better ASE in the practical range of BS density, i.e., 10^1-10^3 BSs/km^2. However, our results show that a smaller UL power compensation factor can greatly boost the ASE in the UL of dense SCNs, i.e., 10^2-10^3 BSs/km^2, while a larger UL power compensation factor is more suitable for sparse SCNs, i.e., 10^1-10^2 BSs/km^2.

Very recent studies showed that in a fully loaded dense small cell network (SCN), the coverage probability performance will continuously decrease with the network densification. Such new results were captured in IEEE ComSoc Technology News with an alarming title of "Will Densification Be the Death of 5G?". In this paper, we revisit this issue from more practical views of realistic network deployment, such as a finite number of active base stations (BSs) and user equipments (UEs), a decreasing BS transmission power with the network densification, etc. Particularly, in dense SCNs, due to an oversupply of BSs with respect to UEs, a large number of BSs can be put into idle modes without signal transmission, if there is no active UE within their coverage areas. Setting those BSs into idle modes mitigates unnecessary inter-cell interference and reduces energy consumption. In this paper, we investigate the performance impact of such BS idle mode capability (IMC) on dense SCNs. Different from existing work, we consider a realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. Moreover, we obtain analytical results for the coverage probability, the area spectral efficiency (ASE) and the energy efficiency (EE) performance for SCNs with the BS IMC and show that the performance impact of the IMC on dense SCNs is significant. As the BS density surpasses the UE density in dense SCNs, the coverage probability will continuously increase toward one, addressing previous concerns on "the death of 5G". Finally, the performance improvement in terms of the EE performance is also investigated for dense SCNs using practical energy models developed in the Green-Touch project., Comment: To appear in IEEE TVT

In this paper, we study the impact of the base station (BS) idle mode capability (IMC) on the network performance in dense small cell networks (SCNs). Different from existing works, we consider a sophisticated path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE) performance for SCNs with IMCs at the BSs. The upper bound, the lower bound and the approximate expression of the activated BS density are also derived. The performance impact of the IMC is shown to be significant. As the BS density surpasses the UE density, thus creating a surplus of BSs, the coverage probability will continuously increase toward one. For the practical regime of the BS density, the results derived from our analysis are distinctively different from existing results, and thus shed new light on the deployment and the operation of future dense SCNs., Comment: final IEEE version: http://ieeexplore.ieee.org/document/7842302/. arXiv admin note: substantial text overlap with arXiv:1609.07710, arXiv:1611.01869

In this paper, a new framework of mobile converged networks is proposed for flexible resource optimization over multi-tier wireless heterogeneous networks. Design principles and advantages of this new framework of mobile converged networks are discussed. Moreover, mobile converged network models based on interference coordination and energy efficiency are presented and the corresponding optimization algorithms are developed. Furthermore, future challenges of mobile converged networks are identified to promote the study in modeling and performance analysis of mobile converged networks., Comment: 17 pages, 6 figures

In this article, a network model incorporating both line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions is proposed to investigate impacts of blockages in urban areas on heterogeneous network coverage performance. Results show that co-existence of NLOS and LOS transmissions has a significant impact on network performance. We find in urban areas, that deploying more BSs in different tiers is better than merely deploying all BSs in the same tier in terms of coverage probability., Comment: 6 pages, 2 figures; Accepted by IEEE ICC 2016

The cooperative transmission is an effective approach for vehicular communications to improve the wireless transmission capacity and reliability in the fifth generation (5G) small cell networks. Based on distances between the vehicle and cooperative small cell BSs, the cooperative probability and the coverage probability have been derived for 5G cooperative small cell networks where small cell base stations (BSs) follow Poisson point process distributions. Furthermore, the vehicular handoff rate and the vehicular overhead ratio have been proposed to evaluate the vehicular mobility performance in 5G cooperative small cell networks. To balance the vehicular communication capacity and the vehicular handoff ratio, an optimal vehicular overhead ratio can be achieved by adjusting the cooperative threshold of 5G cooperative small cell networks., Comment: 13 pages, 11 figures

In this paper, we propose a new approach of network performance analysis, which is based on our previous works on the deterministic network analysis using the Gaussian approximation (DNA-GA). First, we extend our previous works to a signal-to-interference ratio (SIR) analysis, which makes our DNA-GA analysis a formal microscopic analysis tool. Second, we show two approaches for upgrading the DNA-GA analysis to a macroscopic analysis tool. Finally, we perform a comparison between the proposed DNA-GA analysis and the existing macroscopic analysis based on stochastic geometry. Our results show that the DNA-GA analysis possesses a few special features: (i) shadow fading is naturally considered in the DNAGA analysis; (ii) the DNA-GA analysis can handle non-uniform user distributions and any type of multi-path fading; (iii) the shape and/or the size of cell coverage areas in the DNA-GA analysis can be made arbitrary for the treatment of hotspot network scenarios. Thus, DNA-GA analysis is very useful for the network performance analysis of the 5th generation (5G) systems with general cell deployment and user distribution, both on a microscopic level and on a macroscopic level., Comment: Final IEEE version: http://ieeexplore.ieee.org/document/7511618/

Traditional ultra-dense wireless networks are recommended as a complement for cellular networks and are deployed in partial areas, such as hotspot and indoor scenarios. Based on the massive multiple-input multi-output (MIMO) antennas and the millimeter wavecommunication technologies, the 5G ultra-dense cellular network is proposed to deploy in overall cellular scenarios. Moreover, a distribution network architecture is presented for 5G ultra-dense cellular networks. Furthermore, the backhaul network capacity and the backhaul energy efficiency of ultra-dense cellular networks are investigated to answer an important question, i.e., how much densification can be deployed for 5G ultra-dense cellular networks. Simulation results reveal that there exist densification limits for 5G ultra-dense cellualr networks with backhaul network capacity and backhaul energy efficiency constraints., Comment: 14 pages, 4 figures

In this paper, we analytically derive an upper bound on the error in approximating the uplink (UL) single-cell interference by a lognormal distribution in frequency division multiple access (FDMA) small cell networks (SCNs). Such an upper bound is measured by the Kolmogorov Smirnov (KS) distance between the actual cumulative density function (CDF) and the approximate CDF. The lognormal approximation is important because it allows tractable network performance analysis. Our results are more general than the existing works in the sense that we do not pose any requirement on (i) the shape and/or size of cell coverage areas, (ii) the uniformity of user equipment (UE) distribution, and (iii) the type of multi-path fading. Based on our results, we propose a new framework to directly and analytically investigate a complex network with practical deployment of multiple BSs placed at irregular locations, using a power lognormal approximation of the aggregate UL interference. The proposed network performance analysis is particularly useful for the 5th generation (5G) systems with general cell deployment and UE distribution., Comment: Final IEEE version: http://ieeexplore.ieee.org/document/7426421/. arXiv admin note: text overlap with arXiv:1505.01924

In this paper, for the first time, we analytically prove that the uplink (UL) inter-cell interference in frequency division multiple access (FDMA) small cell networks (SCNs) can be well approximated by a lognormal distribution under a certain condition. The lognormal approximation is vital because it allows tractable network performance analysis with closed-form expressions. The derived condition, under which the lognormal approximation applies, does not pose particular requirements on the shapes/sizes of user equipment (UE) distribution areas as in previous works. Instead, our results show that if a path loss related random variable (RV) associated with the UE distribution area, has a low ratio of the 3rd absolute moment to the variance, the lognormal approximation will hold. Analytical and simulation results show that the derived condition can be readily satisfied in future dense/ultra-dense SCNs, indicating that our conclusions are very useful for network performance analysis of the 5th generation (5G) systems with more general cell deployment beyond the widely used Poisson deployment., Comment: Final IEEE version: http://ieeexplore.ieee.org/document/7417160/

In this paper, we introduce a sophisticated path loss model into the stochastic geometry analysis incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to study their performance impact in small cell networks (SCNs). Analytical results are obtained on the coverage probability and the area spectral efficiency (ASE) assuming both a general path loss model and a special case of path loss model recommended by the 3rd Generation Partnership Project (3GPP) standards. The performance impact of LoS and NLoS transmissions in SCNs in terms of the coverage probability and the ASE is shown to be significant both quantitatively and qualitatively, compared with previous work that does not differentiate LoS and NLoS transmissions. Particularly, our analysis demonstrates that when the density of small cells is larger than a threshold, the network coverage probability will decrease as small cells become denser, which in turn makes the ASE suffer from a slow growth or even a notable decrease. For practical regime of small cell density, the performance results derived from our analysis are distinctively different from previous results, and shed new insights on the design and deployment of future dense/ultra-dense SCNs., Comment: Final IEEE version: http://ieeexplore.ieee.org/document/7416981/. arXiv admin note: substantial text overlap with arXiv:1503.04251

In this paper, we introduce a sophisticated path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to study their impact on the performance of dense small cell networks (SCNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE), assuming both a general path loss model and a special case with a linear LoS probability function. The performance impact of LoS and NLoS transmissions in dense SCNs in terms of the coverage probability and the ASE is significant, both quantitatively and qualitatively, compared with the previous work that does not differentiate LoS and NLoS transmissions. Our analysis demonstrates that the network coverage probability first increases with the increase of the base station (BS) density, and then decreases as the SCN becomes denser. This decrease further makes the ASE suffer from a slow growth or even a decrease with network densification. The ASE will grow almost linearly as the BS density goes ultra dense. For practical regime of the BS density, the performance results derived from our analysis are distinctively different from previous results, and thus shed new insights on the design and deployment of future dense SCNs., Comment: 32 pages, 8 figures, IEEE TWC [J]

Cell association scheme determines which base station (BS) and mobile user (MU) should be associated with and also plays a significant role in determining the average data rate a MU can achieve in heterogeneous networks. However, the explosion of digital devices and the scarcity of spectra collectively force us to carefully re-design cell association scheme which was kind of taken for granted before. To address this, we develop a new cell association scheme in heterogeneous networks based on joint consideration of the signal-to-interference-plus-noise ratio (SINR) which a MU experiences and the traffic load of candidate BSs1. MUs and BSs in each tier are modeled as several independent Poisson point processes (PPPs) and all channels experience independently and identically distributed ( i.i.d.) Rayleigh fading. Data rate ratio and traffic load ratio distributions are derived to obtain the tier association probability and the average ergodic MU data rate. Through numerical results, We find that our proposed cell association scheme outperforms cell range expansion (CRE) association scheme. Moreover, results indicate that allocating small sized and high-density BSs will improve spectral efficiency if using our proposed cell association scheme in heterogeneous networks., Comment: Accepted by IEEE ICC 2015 - Next Generation Networking Symposium

Raptor codes have been widely used in many multimedia broadcast/multicast applications. However, our understanding of Raptor codes is still incomplete due to the insufficient amount of theoretical work on the performance analysis of Raptor codes, particularly under maximum-likelihood (ML) decoding, which provides an optimal benchmark on the system performance for the other decoding schemes to compare against. For the first time, this paper provides an upper bound and a lower bound, on the packet error performance of Raptor codes under ML decoding, which is measured by the probability that all source packets can be successfully decoded by a receiver with a given number of successfully received coded packets. Simulations are conducted to validate the accuracy of the analysis. More specifically, Raptor codes with different degree distribution and pre-coders, are evaluated using the derived bounds with high accuracy., Comment: 28 pages and 5 figures

Wireless communication in a network of mobile devices is a challenging and resource demanding task, due to the highly dynamic network topology and the wireless channel randomness. This paper investigates information broadcast schemes in 2D mobile ad-hoc networks where nodes are initially randomly distributed and then move following a random direction mobility model. Based on an in-depth analysis of the popular Susceptible-Infectious-Recovered epidemic broadcast scheme, this paper proposes a novel energy and bandwidth efficient broadcast scheme, named the energy-efficient broadcast scheme, which is able to adapt to fast-changing network topology and channel randomness. Analytical results are provided to characterize the performance of the proposed scheme, including the fraction of nodes that can receive the information and the delay of the information dissemination process. The accuracy of analytical results is verified using simulations driven by both the random direction mobility model and a real world trace., Comment: accepted to appear in IEEE Transactions on Wireless Communications

It is a great challenge to evaluate the network performance of cellular mobile communication systems. In this paper, we propose new spatial spectrum and energy efficiency models for Poisson-Voronoi tessellation (PVT) random cellular networks. To evaluate the user access the network, a Markov chain based wireless channel access model is first proposed for PVT random cellular networks. On that basis, the outage probability and blocking probability of PVT random cellular networks are derived, which can be computed numerically. Furthermore, taking into account the call arrival rate, the path loss exponent and the base station (BS) density in random cellular networks, spatial spectrum and energy efficiency models are proposed and analyzed for PVT random cellular networks. Numerical simulations are conducted to evaluate the network spectrum and energy efficiency in PVT random cellular networks., Comment: appears in IEEE Transactions on Communications, April, 2015

Two-tier femtocell networks is an efficient communication architecture that significantly improves throughput in indoor environments with low power consumption. Traditionally, a femtocell network is usually configured to be either completely open or completely closed in that its channels are either made available to all users or used by its own users only. This may limit network flexibility and performance. It is desirable for owners of femtocell base stations if a femtocell can partially open its channels for external users access. In such scenarios, spectrum and energy efficiency becomes a critical issue in the design of femtocell network protocols and structure. In this paper, we conduct performance analysis for two-tier femtocell networks with partially open channels. In particular, we build a Markov chain to model the channel access in the femtocell network and then derive the performance metrics in terms of the blocking probabilities. Based on stationary state probabilities derived by Markov chain models, spectrum and energy efficiency are modeled and analyzed under different scenarios characterized by critical parameters, including number of femtocells in a macrocell, average number of users, and number of open channels in a femtocell. Numerical and Monte-Carlo (MC) simulation results indicate that the number of open channels in a femtocell has an adverse impact on the spectrum and energy efficiency of two-tier femtocell networks. Results in this paper provide guidelines for trading off spectrum and energy efficiency of two-tier femtocell networks by configuring different numbers of open channels in a femtocell.