MISO in Ultra-Dense Networks: Balancing the Tradeoff between User and System Performance

With over-deployed network infrastructures, network densification is shown to hinder the improvement of user experience and system performance. In this paper, we adopt multi-antenna techniques to overcome the bottleneck and investigate the performance of single-user beamforming, an effective method to enhance desired signal power, in small cell networks from the perspective of user coverage probability (CP) and network spatial throughput (ST). Pessimistically, it is proved that, even when multi-antenna techniques are applied, both CP and ST would be degraded and even asymptotically diminish to zero with the increasing base station (BS) density. Moreover, the results also reveal that the increase of ST is at the expense of the degradation of CP. Therefore, to balance the tradeoff between user and system performance, we further study the critical density, under which ST could be maximized under the CP constraint. Accordingly, the impact of key system parameters on critical density is quantified via the derived closed-form expression. Especially, the critical density is shown to be inversely proportional to the square of antenna height difference between BSs and users. Meanwhile, single-user beamforming, albeit incapable of improving CP and ST scaling laws, is shown to significantly increase the critical density, compared to the single-antenna regime.Comment: for journal submissio

Limitation of SDMA in Ultra-Dense Small Cell Networks

Benefitting from multi-user gain brought by multi-antenna techniques, space division multiple access (SDMA) is capable of significantly enhancing spatial throughput (ST) in wireless networks. Nevertheless, we show in this letter that, even when SDMA is applied, ST would diminish to be zero in ultra-dense networks (UDN), where small cell base stations (BSs) are fully densified. More importantly, we compare the performance of SDMA, single-user beamforming (SU-BF) (one user is served in each cell) and full SDMA (the number of served users equals the number of equipped antennas). Surprisingly, it is shown that SU-BF achieves the highest ST and critical density, beyond which ST starts to degrade, in UDN. The results in this work could shed light on the fundamental limitation of SDMA in UDN

The Impact of Antenna Height Difference on the Performance of Downlink Cellular Networks

Capable of significantly reducing cell size and enhancing spatial reuse, network densification is shown to be one of the most dominant approaches to expand network capacity. Due to the scarcity of available spectrum resources, nevertheless, the over-deployment of network infrastructures, e.g., cellular base stations (BSs), would strengthen the inter-cell interference as well, thus in turn deteriorating the system performance. On this account, we investigate the performance of downlink cellular networks in terms of user coverage probability (CP) and network spatial throughput (ST), aiming to shed light on the limitation of network densification. Notably, it is shown that both CP and ST would be degraded and even diminish to be zero when BS density is sufficiently large, provided that practical antenna height difference (AHD) between BSs and users is involved to characterize pathloss. Moreover, the results also reveal that the increase of network ST is at the expense of the degradation of CP. Therefore, to balance the tradeoff between user and network performance, we further study the critical density, under which ST could be maximized under the CP constraint. Through a special case study, it follows that the critical density is inversely proportional to the square of AHD. The results in this work could provide helpful guideline towards the application of network densification in the next-generation wireless networks.Comment: conference submission - Mar. 201

Correlations of Interference and Link Successes in Heterogeneous Cellular Networks

In heterogeneous cellular networks (HCNs), the interference received at a user is correlated over time slots since it comes from the same set of randomly located BSs. This results in the correlations of link successes, thus affecting network performance. Under the assumptions of a K-tier Poisson network, strongest-candidate based BS association, and independent Rayleigh fading, we first quantify the correlation coefficients of interference. We observe that the interference correlation is independent of the number of tiers, BS density, SIR threshold, and transmit power. Then, we study the correlations of link successes in terms of the joint success probability over multiple time slots. We show that the joint success probability is decided by the success probability in a single time slot and a diversity polynomial, which represents the temporal interference correlation. Moreover, the parameters of HCNs have an important influence on the joint success probability by affecting the success probability in a single time slot. Particularly, we obtain the condition under which the joint success probability increases with the BS density and transmit power. We further show that the conditional success probability given prior successes only depends on the path loss exponent and the number of time slots.Comment: 26 pages, 6 figure

Effect of Densification on Cellular Network Performance with Bounded Pathloss Model

In this paper, we investigate how network densification influences the performance of downlink cellular network in terms of coverage probability (CP) and area spectral efficiency (ASE). Instead of the simplified unbounded pathloss model (UPM), we apply a more realistic bounded pathloss model (BPM) to model the decay of signal power caused by pathloss. It is shown that network densification indeed degrades CP when the base station (BS) density $\lambda$ is sufficiently large. This is inconsistent with the result derived using UPM that CP is independent of $\lambda$. Moreover, we shed light on the impact of ultra-dense deployment of BSs on the ASE scaling law. Specifically, it is proved that the cellular network ASE scales with rate $\lambda e^{-\kappa\lambda}$, i.e., first increases with $\lambda$ and then diminishes to be zero as $\lambda$ goes to infinity.Comment: submitted to IEEE Commun. Let

Network Densification in 5G: From the Short-Range Communications Perspective

Besides advanced telecommunications techniques, the most prominent evolution of wireless networks is the densification of network deployment. In particular, the increasing access points/users density and reduced cell size significantly enhance spatial reuse, thereby improving network capacity. Nevertheless, does network ultra-densification and over-deployment always boost the performance of wireless networks? Since the distance from transmitters to receivers is greatly reduced in dense networks, signal is more likely to be propagated from long- to short-range region. Without considering short-range propagation features, conventional understanding of the impact of network densification becomes doubtful. With this regard, it is imperative to reconsider the pros and cons brought by network densification. In this article, we first discuss the short-range propagation features in densely deployed network and verify through experimental results the validity of the proposed short-range propagation model. Considering short-range propagation, we further explore the fundamental impact of network densification on network capacity, aided by which a concrete interpretation of ultra-densification is presented from the network capacity perspective. Meanwhile, as short-range propagation makes interference more complicated and difficult to handle, we discuss possible approaches to further enhance network capacity in ultra-dense wireless networks. Moreover, key challenges are presented to suggest future directions.Comment: submitted to IEEE Commun. Ma

Modeling and Analysis of SCMA Enhanced D2D and Cellular Hybrid Network

Sparse code multiple access (SCMA) has been recently proposed for the future wireless networks, which allows non-orthogonal spectrum resource sharing and enables system overloading. In this paper, we apply SCMA into device-to-device (D2D) communication and cellular hybrid network, targeting at using the overload feature of SCMA to support massive device connectivity and expand network capacity. Particularly, we develop a stochastic geometry based framework to model and analyze SCMA, considering underlaid and overlaid mode. Based on the results, we analytically compare SCMA with orthogonal frequency-division multiple access (OFDMA) using area spectral efficiency (ASE) and quantify closed-form ASE gain of SCMA over OFDMA. Notably, it is shown that system ASE can be significantly improved using SCMA and the ASE gain scales linearly with the SCMA codeword dimension. Besides, we endow D2D users with an activated probability to balance cross-tier interference in the underlaid mode and derive the optimal activated probability. Meanwhile, we study resource allocation in the overlaid mode and obtain the optimal codebook allocation rule. It is interestingly found that the optimal SCMA codebook allocation rule is independent of cellular network parameters when cellular users are densely deployed. The results are helpful in the implementation of SCMA in the hybrid system.Comment: submitted to IEEE Trans. Commu

Access Points in the Air: Modeling and Optimization of Fixed-Wing UAV Network

Fixed-wing unmanned aerial vehicles (UAVs) are of great potential to serve as aerial access points (APs) owing to better aerodynamic performance and longer flight endurance. However, the inherent hovering feature of fixed-wing UAVs may result in discontinuity of connections and frequent handover of ground users (GUs). In this work, we model and evaluate the performance of a fixed-wing UAV network, where UAV APs provide coverage to GUs with millimeter wave backhaul. Firstly, it reveals that network spatial throughput (ST) is independent of the hover radius under real-time closest-UAV association, while linearly decreases with the hover radius if GUs are associated with the UAVs, whose hover center is the closest. Secondly, network ST is shown to be greatly degraded with the over-deployment of UAV APs due to the growing air-to-ground interference under excessive overlap of UAV cells. Finally, aiming to alleviate the interference, a projection area equivalence (PAE) rule is designed to tune the UAV beamwidth. Especially, network ST can be sustainably increased with growing UAV density and independent of UAV flight altitude if UAV beamwidth inversely grows with the square of UAV density under PAE

Cognitive Learning of Statistical Primary Patterns via Bayesian Network

In cognitive radio (CR) technology, the trend of sensing is no longer to only detect the presence of active primary users. A large number of applications demand for more comprehensive knowledge on primary user behaviors in spatial, temporal, and frequency domains. To satisfy such requirements, we study the statistical relationship among primary users by introducing a Bayesian network (BN) based framework. How to learn such a BN structure is a long standing issue, not fully understood even in the statistical learning community. Besides, another key problem in this learning scenario is that the CR has to identify how many variables are in the BN, which is usually considered as prior knowledge in statistical learning applications. To solve such two issues simultaneously, this paper proposes a BN structure learning scheme consisting of an efficient structure learning algorithm and a blind variable identification scheme. The proposed approach incurs significantly lower computational complexity compared with previous ones, and is capable of determining the structure without assuming much prior knowledge about variables. With this result, cognitive users could efficiently understand the statistical pattern of primary networks, such that more efficient cognitive protocols could be designed across different network layers.Comment: This paper has been refreshed with a new versio

On throughput capacity for a class of buffer-limited MANETs

Available throughput performance studies for mobile ad hoc networks (MANETs) suffer from two major limitations: they mainly focus on the scaling law study of throughput, while the exact throughput of such networks remains largely unknown; they usually consider the infinite buffer scenarios, which are not applicable to the practical networks with limited buffer. As a step to address these limitations, this paper develops a general framework for the exact throughput capacity study of a class of buffer-limited MANETs with the two-hop relay. We first provide analysis to reveal how the throughput capacity of such a MANET is determined by its relay-buffer blocking probability (RBP). Based on the Embedded Markov Chain Theory and Queuing Theory, a novel theoretical framework is then developed to enable the RBP and closed-form expression for exact throughput capacity to be derived. We further conduct case studies under two typical transmission scheduling schemes to illustrate the applicability of our framework and to explore the corresponding capacity optimization as well as capacity scaling law. Finally, extensive simulation and numerical results are provided to validate the efficiency of our framework and to show the impacts brought by the buffer constraint