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In this letter, we analyze the coverage performance of multi-user multiple-input multiple-output (MU-MIMO) downlink cellular networks. We model the locations of the base stations and mobile users using Poisson Point Processes and employ maximum ratio transmission precoding at the base station. Our analysis builds upon Prony’s method to approximately calculate the coverage probability using the sum of exponentials which facilitates the computation of Laplace transform of both intra-cell and inter-cell interference. We demonstrate the accuracy of derived approximate coverage probability expressions through numerical simulations for different MU-MIMO configurations. [ABSTRACT FROM AUTHOR]

Mobile nodes are promising radio frequency energy sources due to their growing numbers. Simulating energy harvesting from mobile nodes is time consuming, so theoretical results are important. In this letter, we theoretically analyze the radio signal energy harvested from mobile and fixed nodes. We assume that the locations of the fixed nodes and those of randomly appearing mobile nodes follow Poisson Point Processes (PPPs). We derived the closed form formulas of the first and second moments of the total energy harvested at a typical node from other nodes and propose the approximation of the complementary cumulative distribution function (CCDF) of this total energy. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) can be used as flying base stations (BSs) to offload Macro-BSs in hotspots. However, due to the limited battery on-board, UAVs can typically stay in operation for less than 1.5 hours. Afterward, the UAV has to fly back to a dedicated charging station that recharges/replaces the UAV’s battery. In this letter, we study the performance of a UAV-enabled cellular network while capturing the influence of the spatial distribution of the charging stations. In particular, we use tools from stochastic geometry to derive the coverage probability of a UAV-enabled cellular network as a function of the battery size, the density of the charging stations, and the time required for recharging/replacing the battery. [ABSTRACT FROM AUTHOR]

This letter studies a wireless peer discovery system where peers are equipped with more than one antenna. Wireless peer discovery is a network operation performed to identify the existence of peers in the network. In this operation, some fractions of the peers broadcast the discovery message to nearby peers. In such a system, our aim is to minimize the overall consumed power in the network. The consumed power is composed of two parts: transmit power and circuit power. The circuit power is dependent on the number of active antennas which are to be optimized while keeping the average number of discovered peers greater than a certain threshold. The problem is non-convex and difficult to solve. In this regard, a low complexity algorithm is proposed which utilizes bisection search. Numerical results demonstrate that the proposed algorithm achieves almost the same performance as the optimal exhaustive search algorithm with much reduced complexity. [ABSTRACT FROM AUTHOR]

Effect of interference correlation on wireless systems is often studied by modeling the locations of interferers as a Poisson point process (PPP). However, in many cases, the complicated nature of this correlation limits the analytical tractability of the PPP-based approach. For example, for an interference-aware $N$ -antenna maximum-ratio combining (MRC) receiver, the analytical expression for outage probability is available only for $N=2$. For $N>2$ , the exact analysis using the standard PPP-based approach becomes intractable because of which one has to either resort to bounds or to simulations. In this letter, we overcome this issue and derive the MRC outage probability for an arbitrary $N$ by employing the mixture-based method of modeling the correlation in the interference powers. This method offers a much simpler analytical structure to the correlated interference, thereby lending analytical tractability to such analyses. The mixture parameter ($q$) is tuned based on the matching of joint signal-to-interference ratio (SIR) statistics, which results in a very accurate mixture-based result. The tightness of these approximations is verified using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

As the interference in PPP-based wireless networks exhibit spatial correlation, any joint analysis involving multiple spatial points either end up with numerical integrations over \mathbb R^2 or become analytically too intractable. To tackle these issues, we present an alternate approach which not only offers a simpler analytical structure, but also closely mimics the PPP characteristics. This approach at its core models the correlated interferences using a correlation framework constructed using random variable mixtures. In addition, a correlation framework based on the more standard method of linear combination of random variables is also presented for comparison purpose. The performance of these models is studied by deriving the joint complementary cumulative distribution function of signal-to-interference ratios at $N$ arbitrary points. The plots are found to tightly approximate the exact PPP-based results, with the tightness depending on the values of $\lambda p$ (interferer intensity), $\alpha $ (path loss exponent), and $N$ . The applicability of the mixture-based model is also shown for a multi-antennae MRC receiver where only major derivation steps that simplify the outage probability analysis are shown. [ABSTRACT FROM PUBLISHER]

Stochastic geometry provides a convenient approach to analyze the cellular networks. Adoption of Poisson point process, for example, has been proven to be an efficient tool to obtain the pessimistic bounds of the capacity and outage probability in the downlink channel. However, due to the correlated distribution of the interfering users, analysis of uplink communication has never been an easy task. Although some of the current literature has attempted to resolve this problem by assuming suitable interferer distributions, an accurate yet tractable description of the uplink user process has always been sought after. In this letter, we provide an exact description of the uplink user process by characterizing the counting measure in an arbitrary bounded Borel set. For computational tractability, we obtain an approximation of the exact result and verify its accuracy through Monte Carlo simulation. [ABSTRACT FROM PUBLISHER]

As part of the 5G communication paradigm, ultra reliable communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. While most existing studies on reliable communication do not investigate this problem from a dependability theory perspective, those dependability-based studies tend to define reliability merely in the time domain. In this letter, we advocate extending the concept of URC from the dependability perspective also in the space domain. We initiate definitions on cell availability and system availability. The availability and the probability of providing a guaranteed level of availability in a network are analyzed both/either cell-wise and/or system-wise. Poisson point process and Voronoi tessellation are adopted to model the spatial characteristics of cell deployment in both homogeneous and heterogeneous networks. [ABSTRACT FROM PUBLISHER]

In heterogeneous cellular network (HCN), mobile users may travel across the coverage of different base stations (BSs). Handoff procedures need to be performed to maintain seamless connectivity. Since BSs in different tiers have distinct setting about transmission power and range extension bias, analysis for the network performance becomes complicated, particularly for the vertical handoff as an important functionality in HCN. To facilitate performance analysis, this letter proposes a method built on the equivalence between vertical handoff and horizontal handoff events. With the established equivalence, both types of handoff probabilities can be obtained in a single analytical framework. We also derive the coverage probability of mobile users by including the handoff cost in the analysis and obtain a compact expression. Numerical results are presented to validate the analysis accuracy and provide insights to the performance of HCN in supporting mobility. [ABSTRACT FROM PUBLISHER]

Modeling the base station deployments with stochastic geometry in the cellular network, we derive the coverage probability and average rate of typical user under a generalized composite fading channel, which is composed of the shadowing and Nakagami- m fading. Unlike the previous work, the current coverage analysis does not involve any numerical integration, allowing for a rather straightforward evaluation of the required signal-to-interference ratio with the given target cellular performance under general channel environments. It approximates a gamma-lognormal distribution, which characterizes an effect of composite fading, as a weighted sum of gamma distributions by the Gaussian-Hermite quadrature for analytical tractability. [ABSTRACT FROM PUBLISHER]

A novel virtual small cells formation approach for the fifth-generation mobile network is proposed in which a subset of qualified users is selected to serve as the base stations of virtual small cells in connecting other users to the macrocell base stations. In the proposed approach, the optimum virtual small cell density is obtained, so that the number of required communication links to the macrocell base stations for connecting all users directly or through small cells is minimized. It is shown that by using the proposed virtual small cell technique, the number of connections to the macrocell base stations becomes proportional to the logarithm of the user density. Since this relationship is linear in conventional cellular networks, utilization of virtual small cells can significantly increase the overall network capacity. In addition, the optimum virtual small cell density is derived for cases where the communications costs for a user-to-macrocell direct link and a small cell-to-macrocell trunk link are not the same. [ABSTRACT FROM PUBLISHER]

Instead of assuming fully loaded cells in the analysis on cache-enabled networks with tools of stochastic geometry, we focus on the dynamic traffic in this letter. With modeling traffic dynamics of request arrivals and departures, probabilities of full-, free-, and modest-load cells in the large-scale cache-enabled network are elaborated based on the traffic queue state. Moreover, we propose to exploit the packets cached at cache-enabled users as side information to cancel the incoming interference. Then, the packet loss rates for both the cache-enabled and cache-untenable users are investigated. The simulation results verify our analysis. [ABSTRACT FROM PUBLISHER]

This letter investigates the uplink spectral efficiency (SE) of a two-tier cellular network, where massive multiple-input multiple-output macro base stations are overlaid with dense small cells. Macro user equipments (MUEs) and small cells with single user equipment uniformly scattered are modeled as two independent homogeneous Poisson point processes. By applying stochastic geometry, we analyze the multiuser uplink SE at a macro base station that employs a zero-forcing detector and we obtain a novel lower bound as well as its approximation. According to the simple and near-exact analytical expression, we observe that the ideal way to improve the SE is by increasing the MUE density and the base station antennas synchronously rather than increasing them individually. Furthermore, a large value of path loss exponent has a positive effect on the SE due to the reduced aggregated interference. [ABSTRACT FROM PUBLISHER]

The statistics of the ratio between the propagation losses of a given node and its $i$-th and $j$-th least-propagation-loss neighbors are obtained assuming that the spatial distribution of the neighboring nodes follows a two-dimensional homogeneous Poisson point process. It is shown that these statistics, unlike those for each individual propagation loss, are independent of the environmental fading type as well as the density of the neighbor nodes. The analytical results are validated and illustrated through numerical results and computer simulations. Some applications of the derived statistics are also presented. [ABSTRACT FROM PUBLISHER]

Cellular networks are now nearly universally deployed and are under ever-growing pressure to increase the volume of data deliverable to consumers. Understanding how base stations (BSs) are spatially deployed could prominently facilitate the performance analyses of cellular networks, as well as the design of efficient networking protocols. In this letter, inspired by the clustering reality of BSs and the intrinsic heavy-tailed characteristics of human activities, we aim to re-examine the statistical pattern of BSs in cellular networks, and find the most appropriate spatial density distribution of BSs. Interestingly, by taking advantage of large amount of realistic deployment information of BSs from on-operating cellular networks, we find that the widely adopted Poisson distribution severely diverges from the practical density distribution of BSs. Instead, heavy-tailed distributions could more precisely match the practical distribution. In particular, $\alpha$-stable distribution, the distribution also found in traffic pattern of broadband networks and cellular networks, is most consistent with the practical one. [ABSTRACT FROM PUBLISHER]

Energy efficiency in wireless communication systems has recently attracted great interest. Small-sized cell topology is a key idea for energy saving. In this letter, we characterize the scaling laws of energy efficiency related metrics such as base station (BS) transmit power, capacity per user, and energy efficiency per user for varying cell radii in downlink cellular networks by investigating the asymptotic behaviors. The scaling laws of the BS transmit power per user, capacity per user, and energy efficiency per user follow R^γ-2, R^{-2}, and R^{-γ}, respectively, where R is the cell radius and γ denotes the path loss exponent. [ABSTRACT FROM PUBLISHER]

We study the spatial distribution of transmit powers and signal to interference plus noise ratio (SINR) in device-to-device (D2D) networks. Using homogeneous Poisson Point Processes (PPP), cumulative distribution function (CDF) of the transmit power and SINR are analytically derived for a D2D network employing power control. Then, computer simulations are performed for the same network architecture and it is shown that device location modeling and analytical methods from stochastic geometry can enable us to obtain transmit power and SINR distributions of a D2D network. [ABSTRACT FROM PUBLISHER]

Interference in wireless systems is both temporally and spatially correlated. Yet very little research has analyzed the effect of such correlation. Here we focus on its impact on the diversity in Poisson networks with multi-antenna receivers. Most work on multi-antenna communication does not consider interference, and if it is included, it is assumed independent across the receive antennas. Here we show that interference correlation significantly reduces the probability of successful reception over SIMO links. The diversity loss is quantified via the diversity polynomial. For the two-antenna case, we provide the complete joint SIR distribution. [ABSTRACT FROM PUBLISHER]

Nearest neighbor forwarding (NNF) intends to maximize throughput in wireless networks. However, NNF suffers from low one-hop progress and may therefore significantly increase end-to-end delay. The spatial efficiency (SE), i.e., the expectation of the ratio of progress to interference area associated with one hop, is introduced in order to quantify this trade-off. The problem of low progress is addressed by maximizing the one-hop SE, subject to the central angle γ, determining the forwarding area. By this, the optimal balance between minimizing the interference area and maximizing progress is found. Then, this analysis is extended by considering a Poisson point process, driven by some traffic intensity, on the interference area. Furthermore, the traffic aware γ*-NNF strategy is proposed which adapts γ to the traffic intensity in order to maximize SE. Simulation results show a significant reduction of the end-to-end delay if γ*-NNF is used. [ABSTRACT FROM PUBLISHER]

We consider a Poisson network of sources, each with a destination at a given distance and a buffer of infinite capacity. Assuming independent Bernoulli arrivals, we characterize the stability region when one or two classes of users are present in the network. We then derive a fixed-point equation that determines the success probability of the typical source-destination link and evaluate the mean delay at each buffer. [ABSTRACT FROM PUBLISHER]