Performance Of Small Cell Networks Research Articles

Outage performance and optimal design of MIMO-NOMA enhanced small cell networks with imperfect channel-state information

This paper focuses on boosting the performance of small cell networks (SCNs) by integrating multiple-input multiple-output (MIMO) and nonorthogonal multiple access (NOMA) in consideration of imperfect channel-state information (CSI). The estimation error and the spatial randomness of base stations (BSs) are characterized by using Kronecker model and Poisson point process (PPP), respectively. The outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies, including random grouping and distance-based grouping. It is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime, while the outage performance deteriorates if the intensity is sufficiently low. Besides, as the channel uncertainty lessens, the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell interference. Moreover, highly correlated estimation error ameliorates the outage performance under a low quality of CSI, otherwise it behaves oppositely. Afterwards, the goodput is maximized by choosing appropriate precoding matrix, receiver filters and transmission rates. In the end, the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.

A new look on performance of small-cell network with design of multiple antennas and full-duplex

A downlink of small-cell network is studied in this paper studies in term of outage performance. We benefit by design of multiple antennas at the base station and fullduplex transmission mode. The scenario of multiple surrounded small-cell networks is considered to look the impact of interference. We derive the closed-form expression of outage probability to show performance of mobile user. We investigate target rate is main factor affecting to outage performance. According to the considered system, simulation results indicate reasonable value of outage probability and throughput as well. Finally, Monte-Carlo simulation method is deployed to determine exactness of main results found in this article. Finally, the considered system can exhibit improved performance if controlling interference term.

Leveraging the Coupling of Radio Access Network and mmWave Backhaul Network: Modeling and Optimization

Capable of supporting the on-demand high-rate connection towards the core network, wireless millimeter wave (mmWave) backhaul becomes an appealing solution with the growing deployment of small cell base stations (BSs). However, the application of wireless backhaul would impose great limitations on the admission of BSs and the access rate, resulting in a tight coupling between backhaul and radio access network (RAN). In this light, we comprehensively investigate the performance of small cell networks (SCN) in terms of network spatial throughput (ST), supposing that backhaul is conveyed from gateways to BSs through mmWave links. Our results show that the coupling effect makes network ST in the RAN greatly dependent on gateway density λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</sub> and suffer exponential degradation with over-provision of backhaul. It manifests that, if excessive backhaul capacity is provided by deploying more gateways, the exacerbating BS-generated interference deteriorates spatial reuse gain, thereby degrading network ST. Thus, leveraging the coupling between backhaul and RAN, we further conduct a joint optimization of BS and gateway densities to improve network ST. Remarkably, the optimization could mitigate the dependence of network ST on λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</sub> and brings a 2-fold increase in network ST, which is inversely proportional to mmWave beamforming beamwidth.

Exact outage performance of small-cell network relying device-to-device and non-orthogonal multiple access under perfect and imperfect CSI

This paper investigates a non-orthogonal multiple access (NOMA) technique by employing device-to-device (D2D) transmission in small-cell networks. More specifically, the D2D transmission combines the relay selection model from a group of macro base stations (MBS) with the D2D mode in in small-cell network to form a D2D-NOMA system. Such D2D transmission needs assistance from multiple MBS and the small-cell base station (SBS) using decode-and-forward (DF) techniques. In this context, full-duplex (FD) is adopted at intermediate nodes. Furthermore, there are two possible scenarios in practice including perfect channel state information (CSI) and imperfect CSI that need to be studied to examine performance degradation in such considered network. To evaluate system performance, we derive expressions of outage probability for D2D user. Our study results show that the proposed network with more MBSs selection can improve the outage performance compared to the conventional orthogonal multiple access (OMA) scheme. Finally, numerical results confirms the accuracy of the derived expressions.

Delay Analysis of Random Scheduling and Round Robin in Small Cell Networks

We analyze the delay performance of small cell networks operating under random scheduling (RS) and round Robin (RR) protocols. Based on stochastic geometry and queuing theory, we derive accurate and tractable expressions for the distribution of mean delay, which accounts for the impact of random traffic arrivals, queuing interactions, and failed packet retransmissions. Our analysis asserts that RR outperforms RS in terms of mean delay, regardless of traffic statistic. Moreover, the gain from RR is more pronounced in the presence of heavy traffic, which confirms the importance of accounting fairness in the design of scheduling policy. We also find that constrained on the same delay outage probability, RR is able to support more user equipments than that of RS, demonstrating it as an appropriate candidate for the traffic scheduling policy of Internet-of-Things network.

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.

The impact of breakdowns disciplines and repeated attempts on performances of Small Cell Networks

This paper aims at presenting an approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels. We consider the classical disciplines namely, active and dependent breakdowns and moreover we propose new breakdowns disciplines, in which we give to the interrupted customers due to a channel failure, a higher priority compared to other customers. To this end, we use the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation, for the different breakdowns disciplines with and without priority, of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and the channels allocation in as small cell, neither generating nor storing the reachability set. In addition, we develop the formulas of the main stationary performance and reliability indices, as a function of the network parameters, the stationary probabilities and independently of the reachability set markings. Through numerical examples, we discuss the effect of retrials, breakdowns disciplines and the priority on performances.