Small Cell Base Station Density Research Articles

Decoupled UL/DL User Association in Wireless-Powered HetNets With Full-Duplex Small Cells

In this paper, we propose two downlink (DL)-uplink (UL) decoupled (DUDe) user association schemes in wireless-powered full-duplex (FD) heterogeneous networks (HetNets). We consider a two-tier HetNet comprising of half-duplex (HD) massive multi-antenna macrocell base stations (MBSs) and dual-antenna FD small cell base stations (SBSs) to support UL and DL transmissions of FD user equipments (UEs). Each FD UE is first associated to one MBS/SBS, based on the mean maximum received power (MMP) scheme or maximum received power (MRP) to harvest energy. During the consecutive data transmission phase, UEs choose to receive DL traffic from the same MBSs/SBSs as that associated with during energy harvesting phase, and send UL traffic through the same/another SBS. Leveraging tools from the stochastic geometry, we develop an analytical framework to analyze the average harvested energy and derive expressions for the UL and DL coverage probabilities of the proposed DUDe user association schemes. Our results show that there is an optimal value for the SBS density in the wireless-powered FD HetNets, at which both DL and UL coverage probabilities are maximized. Moreover, by applying MMPA and MRPA scheme, wireless-powered FD HetNets with DUDe achieves up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$138.78\%$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$83.37\%$</tex-math></inline-formula> energy efficiency gain over the FD HetNets with DL/UL coupled user association scheme and without wireless power transfer, respectively.

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

AbstractUltra‐dense networks (UDNs) which comprise of small and macro cells, are considered the principal solution for increasing demands of data. However, making energy efficient networks will be a challenge for researchers. In this article, a hybrid optimization technique is proposed to enhance the energy efficiency (EE) of the UDNs, considering the user correlation and hybrid optimization of the density and transmitting power of the small‐cell‐base‐station (SBS). More precisely, the problem framed is a problem of convex‐linear programming and hence is divided into two sub‐problems: cell correlation and hybrid optimization. The expression for the EE of the system is derived in the closed‐form as a factor of the density of SBSs and small cell‐range‐development (CRD) bias dependent on the Poisson point process (PPP) followed by the sequential‐search‐algorithm to improve the small CRD bias and SBS density correspondingly. Additionally, to realize hybrid optimization of the small CRD bias and density of SBSs, a heuristic algorithm is put forward to accomplish the EE of the system. It is revealed from the simulation outcomes that the proposed small CRD bias and SBS density hybrid optimization significantly enhances the EE of the system with low computational intricacy.

Joint uplink and downlink power allocation for maximizing the energy efficiency in ultra-dense networks

Ultra-dense network (UDN) is a promising solution to meet the huge data requirements of future 5G wireless communication systems. With many irregularly deployed small cell base stations (SBSs), it is very difficult to accurately measure network energy efficiency (EE) in UDN. Considering the necessity of saving energy in modern-day networks, in this paper, I present the EE evaluation of UDN based on the random spatial network model. In this considered system, the SBSs and the macro cell users (MUEs) are modeled as a homogeneous Poisson point process (PPP). Unlike the existing literature, I derive the simple closed-form expressions for the successful transmission probabilities of MUEs and small cells by Laplace transformation. Then, based on the obtained successful transmission probabilities, I derive the closed form expression for EE of the small cells in both uplink and downlink under some practical constraints. Further, to obtain the optimal SBS density in UDN, I propose a joint uplink and downlink power allocation (JUDPA) algorithm. The JUDPA algorithm obtains the maximum EE in small cells by iteratively optimizing the uplink and downlink powers. Our theoretical analysis and simulated results demonstrate the accuracy of the proposed model with better power allocation and less complexity than conventional solutions.

Probabilistic Caching for Small-Cell Networks With Terrestrial and Aerial Users

The support for aerial users has become the focus of recent 3GPP standardizations of 5G, due to their high maneuverability and flexibility for on-demand deployment. In this paper, probabilistic caching is studied for ultra-dense small-cell networks with terrestrial and aerial users, where a dynamic on-off architecture is adopted under a sophisticated path loss model incorporating both line-of-sight and non-line-of-sight transmissions. Generally, this paper focuses on the successful download probability (SDP) of user equipments (UEs) from small-cell base stations (SBSs) that cache the requested files under various caching strategies. To be more specific, the SDP is first analyzed using stochastic geometry theory, by considering the distribution of such two-tier UEs and SBSs as Homogeneous Poisson Point Processes. Second, an optimized caching strategy (OCS) is proposed to maximize the average SDP. Third, the performance limits of the average SDP are developed for the popular caching strategy (PCS) and the uniform caching strategy (UCS). Finally, the impacts of the key parameters, such as the SBS density, the cache size, the exponent of Zipf distribution and the height of aerial user, are investigated on the average SDP. The analytical results indicate that the UCS outperforms the PCS if the SBSs are sufficiently dense, while the PCS is better than the UCS if the exponent of Zipf distribution is large enough. Furthermore, the proposed OCS is superior to both the UCS and PCS.

Performance of Small Cell Networks Under Multislope Bounded Pathloss Model: From Sparse to Ultradense Deployment

Network densification is proved to be the most efficient method to expand network capacity over the past few decades. Nevertheless, can network densification always boost network performance? To shed light on this, we explore the pros and cons of network densification in $k$ -dimension downlink small cell networks by analyzing transmission success probability (SP) and network spatial throughput (ST). Remarkably, different from long-distance propagation in sparse networks, short-distance propagation of distinctive features dominates as well under dense deployment of small cells. On this account, we apply a multislope bounded pathloss model (MBPM) to characterize signal attenuation within long and short propagation distance. Under MBPM, it is surprisingly found that network densification would enhance SP and ST only when small cell base station density $\lambda \left(\mathrm{SBS}/\mathrm{m}^{k}\right)$ is smaller than some critical densities. Beyond the critical densities, both SP and ST are proved to exponentially diminish with $\lambda$ and even approach zero when $\lambda$ is sufficiently large. In other words, ultradense deployment of small cells indeed deteriorates network performance. Besides, the numerically derived critical densities are helpful for the practical deployment of small cell networks.

A Novel Proactive Caching Strategy With Community-Aware Learning in CoMP-Enabled Small-Cell Networks

We propose a novel proactive caching strategy with social community-aware learning in the Coordinated Multi-Point (CoMP)-enabled small-cell network. First, it predicts content request probabilities using community-aware non-negative matrix factorization (CNMF) with implicit feedback. The CNMF-based proactive caching algorithm then makes a caching decision by considering estimated content request probabilities of both the associated and neighbor users to closely cooperate with CoMP. Simulation results show that the proposed caching strategy improves the performance in terms of the content hit ratio and the average content delivery completion time according to the cache size. Furthermore, the performance of the proposed caching with and without CoMP is evaluated by varying the cache size and the small-cell base station density.

Content-Aware Cooperative Transmission in HetNets With Consideration of Base Station Height

With macrocell base stations (MBSs) providing basic coverage for mobile users, the multiple tiers of cache-enabled small-cell base stations (SBSs) can opportunistically form user-centric clusters to enhance network capacity through traffic offloading and cooperative transmission. In this paper, we investigate cooperative transmission in cache-enabled heterogeneous networks considering the impact of base station (BS) heights. Specifically, the user-centric cooperative SBS clusters are formed based on the information of the cached contents, the transmission distance, and the cell load at SBSs. The users failed to be offloaded to the cooperative SBS clusters are served by the nearest MBSs. By incorporating the COST 231 Hata model for the line-of-sight and nonline-of-sight channels, the explicit expressions for the average spectral efficiency (SE) are obtained with statistical characterizations for the cell load distribution, as well as the aggregated information and interference signal strength. The analytical results indicate that with the COST 231 Hata model and the cooperative SBS cluster, the average SE decreases with the increase of BS height. Moreover, different tradeoffs exist with the varying cache size, SBS density, and cooperative distance threshold, which results in a bell-shaped SE with respect to (w.r.t) the SBS density and the cooperative distance threshold. In addition, with an appropriate cooperative distance threshold, the average SE exhibits a bell-shaped relationship w.r.t the cache size. Extensive simulations are conducted to validate the analytical results and demonstrate the impact of the network parameters.

Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.

Capacity- and Trust-Aware BS Cooperation in Nonuniform HetNets: Spectral Efficiency and Optimal BS Density

This paper studies base station (BS) cooperation in nonuniform heterogeneous networks. Considering the limited capacity at BS and existence of untrusted small cell BSs (SBSs) in practical scenarios, a novel capacity- and trust-aware BS cooperation strategy is proposed. The BS cooperation is performed in a user centric manner, based on the average received signal strength at users, the capacity of BSs, and the trustworthiness of SBSs. Furthermore, with the proposed BS cooperation, the statistics of aggregate information-signal strength and interference strength are theoretically analyzed, based on stochastic geometry. Then, expressions for spectral efficiency (SE) and area SE (ASE) are analytically derived. In addition, to study the impact of the SBS density on the SE and ASE, the optimal densities of normal SBSs to maximize the SE and ASE are proved to exist and obtained. Finally, simulations and numerical evaluations validate the theoretical analysis and reveal that with the awareness of BS capacity and trustworthiness, optimal cooperative thresholds achieving the maximum SE and ASE exist, which decrease with high path-loss exponent; and in high path-loss fading environment with high existence probability of untrusted SBSs, more normal SBSs are required to be deployed to achieve the maximum SE and ASE performance.

Outage Analysis of Offloading in Heterogeneous Networks: Composite Fading Channels

Small cells deployment is one of the most significant long-term strategic policies of the mobile network operators. In heterogeneous networks (HetNets), small cells serve as offloading spots in the radio access network to offload macro users (MUs) and their associated traffic from congested macrocells. In this paper, we perform analytical analysis and investigate how the radio propagation effects such as multipath and shadowing and small cell base station density affect MUs' offloading to small cell network (SCN). In particular, we exploit composite fading channels in our evaluation when an MU is offloaded to SCN with varying small and macro cell densities in the stochastic HetNets framework. We derive the expressions for outage probability (equivalently success probability) of the MU in macro network and SCN for two different cases, viz.: i) Nakagami-lognormal channel fading; ii) time-shared (combined) shadowed/unshadowed channel fading. We propose efficient approximations for the probability density functions of the channel fading (power) for the above-mentioned fading distributions that do not have closed-form expressions employing Gauss-Hermite integration and finite exponential series, respectively. Finally, the outage probability performance of MU with and without offloading options/services is analyzed for various settings of fading channels.

Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks.

Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user’s quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities.