Heterogeneous cellular networks: From theory to practice

TL;DR: In this paper, the authors derived a general and closed-form result for the success probability in downlink multiple-antenna (MIMO) heterogeneous cellular networks (HetNets), utilizing a novel Toeplitz matrix representation.

TL;DR: This paper studies an opportunistic transmission scheme and aims to maximize the average throughput for each MU, which jointly exploits the statistics and current states of the channel, battery, and EH rate, together with the availability to the common channel.

TL;DR: The rapid pace of innovations in information and communication technology (ICT) industry over the past decade has greatly improved people’s mobile communication experience and this, in turn, has escalated the number of people using mobile devices.

TL;DR: The conception and characteristics of the IoT are introduced, and the technology requirements for realizing ubiquitous and smart information services are described, as well as the development trends of information technologies and information networks in the next five to ten years.

TL;DR: This paper develops a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density.

Abstract: Cellular networks are in a major transition from a carefully planned set of large tower-mounted base-stations (BSs) to an irregular deployment of heterogeneous infrastructure elements that often additionally includes micro, pico, and femtocells, as well as distributed antennas. In this paper, we develop a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density. Assuming a mobile user connects to the strongest candidate BS, the resulting Signal-to-Interference-plus-Noise-Ratio (SINR) is greater than 1 when in coverage, Rayleigh fading, we derive an expression for the probability of coverage (equivalently outage) over the entire network under both open and closed access, which assumes a strikingly simple closed-form in the high SINR regime and is accurate down to -4 dB even under weaker assumptions. For external validation, we compare against an actual LTE network (for tier 1) with the other K-1 tiers being modeled as independent Poisson Point Processes. In this case as well, our model is accurate to within 1-2 dB. We also derive the average rate achieved by a randomly located mobile and the average load on each tier of BSs. One interesting observation for interference-limited open access networks is that at a given \sinr, adding more tiers and/or BSs neither increases nor decreases the probability of coverage or outage when all the tiers have the same target-SINR.

TL;DR: A tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association policies is developed and the average ergodic rate of the typical user, and the minimum average users throughput - the smallest value among the average user throughputs supported by one cell in each tier is derived.

TL;DR: An overview of the techniques being considered for LTE Release 10 (aka LTEAdvanced) is discussed, which includes bandwidth extension via carrier aggregation to support deployment bandwidths up to 100 MHz, downlink spatial multiplexing including single-cell multi-user multiple-input multiple-output transmission and coordinated multi point transmission, and heterogeneous networks with emphasis on Type 1 and Type 2 relays.