Our traditional notion of a cell is changing dramatically given the increasing degree of heterogeneity in 4G and emerging 5G systems. Rather than belonging to a specific cell, a device would choose the most suitable connection from the plethora of connections available. In such a setting, given the transmission powers differ significantly between downlink (DL) and uplink (UL), a wireless device that sees multiple Base Stations (BSs) may access the infrastructure in a way that it receives the downlink (DL) traffic from one BS and sends uplink (UL) traffic through another BS. This situation is referred to as Downlink and Uplink Decoupling (DUDe). In this paper, the capacity and throughput gains brought by decoupling are rigorously derived using stochastic geometry. Theoretical findings are then corroborated by means of simulation results. A further constituent of this paper is the verification of the theoretically derived results by means of a real-world system simulation platform. Despite theoretical assumptions differing from the very complete system simulator, the trends in the association probabilities and capacity gains are similar. Based on the promising results, we then outline architectural changes needed to facilitate the decoupling of DL and UL.
Notably, the most recent contributions @cite_15 @cite_21 have studied the impact of having a cell association which is different for downlink and uplink. The authors of @cite_15 have investigated the throughput and outage gains via the real-world simulation tool Atoll; the simulation results have yielded important performance gains which increase with an increasing density of small cells. The authors of @cite_21 then studied the association probabilities in more details, i.e. the probabilities that a device would associate i) both DL and UL to the Mcell; ii) DL to Scell and UL to Mcell; iii) DL to Mcell and UL to Scell; and iv) both DL and UL to the Scell.
@cite_15 @cite_21
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This paper proposes an analytical study of the shadowing impact on the outage probability in cellular radio networks. We establish that the downlink other-cell interference factor, f, which is defined here as the ratio of outer cell received power to the inner cell received power, plays a fundamental role in the outage probability. From f, we are able to derive the outage probability of a mobile station (MS) initiating a new call. Taking into account the shadowing, f is expressed as a lognormal random variable. Analytical expressions of the interference factor's mean mf and standard deviation sf are provided in this paper. These expressions depend on the topology of the network characterized by a G factor. We show that shadowing increases the outage probability, and using our analytical method, we are able to quantify this impact. However, we establish that the network topology, or correlated received powers, may limit this increase. In order to expand the downlink (DL) coverage areas of picocells in the presence of an umbrella macrocell, the concept of range expansion has been recently proposed, in which a positive range expansion bias (REB) is added to the DL received signal strengths (RSSs) of picocell pilot signals at user equipments (UEs). Although range expansion may increase DL footprints of picocells, it also results in severe DL inter-cell interference in picocell expanded regions (ERs), because ER picocell user equipments (PUEs) are not connected to the cells that provide the strongest DL RSSs. In this paper, we derive closed-form formulas to calculate appropriate REBs for two different range expansion strategies, investigate both DL and uplink (UL) inter-cell interference coordination (ICIC) to enhance picocell performance, and propose a new macrocell-picocell cooperative scheduling scheme to mitigate both DL and UL interference caused by macrocells to ER PUEs. Simulation results provide insights on REB selection approaches at picocells, and demonstrate the benefits of the proposed macrocell-picocell cooperative scheduling scheme over alternative approaches. In this paper we study the performance of cellular networks when their base stations have an unlimited number of antennas. In previous work, the asymptotic behavior of the signal to interference plus nose ratio (SINR) was obtained. We revisit these results by deriving the rigorous expression for the SINR of both downlink and uplink in the scenario of infinite number of antennas. We show that the contamination of the channel estimates happens whenever a pilot sequence is received at a base station simultaneously with non-orthogonal signals coming from other users. We propose a method to avoid such simultaneous transmissions from adjacent cells, thus significantly decreasing interference. We also investigate the effects of power allocation in this interference-limited scenario, and show that it results in gains of over 15dB in the signal to interference ratio for the scenario simulated here. The combination of these two techniques results in rate gains of about 18 times in our simulations. In this paper we develop a tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association policies. The HCN is modeled as a multi-tier cellular network where each tier's base stations (BSs) are randomly located and have a particular transmit power, path loss exponent, spatial density, and bias towards admitting mobile users. For example, as compared to macrocells, picocells would usually have lower transmit power, higher path loss exponent (lower antennas), higher spatial density (many picocells per macrocell), and a positive bias so that macrocell users are actively encouraged to use the more lightly loaded picocells. In the present paper we implicitly assume all base stations have full queues; future work should relax this. For this model, we derive the outage probability of a typical user in the whole network or a certain tier, which is equivalently the downlink SINR cumulative distribution function. The results are accurate for all SINRs, and their expressions admit quite simple closed-forms in some plausible special cases. We also derive the average ergodic rate of the typical user, and the minimum average user throughput - the smallest value among the average user throughputs supported by one cell in each tier. We observe that neither the number of BSs or tiers changes the outage probability or average ergodic rate in an interference-limited full-loaded HCN with unbiased cell association (no biasing), and observe how biasing alters the various metrics.