A holistic view on hyper-dense heterogeneous and small cell networks

Hwang, In-Sun; Song, Byung Cheol; Soliman, S.S.

doi:10.1109/mcom.2013.6525591

Cited by 488 publications

(240 citation statements)

References 9 publications

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“…Again, it is worth comparing against the Marzetta's M j → ∞ regime, by considering the symmetric case where SNR j and ν j are identical for all BS, and where ν j = ν = S /M → 0. In the limit ν → 0, the CBF SINR expression (25) also coincides with the ZFBF SINR expression (26). Also, they both converge to the well-known massive MIMO expression (17) in [4] only in the case that the associated large-scale gains G (q(k)) in (11) are the same for all l. Again, although in the limit of ν j → 0 for all j the SINRs with ZFBF and CBF coincide [4], in the practical regime involving nonzero spatial loads (finite M j 's), ZFBF yields substantial performance benefits [6].…”

Section: Achievable Rates For Large But Finite Numbers Of Antennasmentioning

confidence: 64%

Massive MIMO Technologies and Challenges towards 5G

Papadopoulos¹,

Wang²,

Bursalioglu³

et al. 2016

IEICE Trans. Commun.

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SUMMARY Massive MIMO is widely recognized as an essential technology for 5G. Together with newly allocated spectrum (bandwidth) and network densification (small cells), it is expected to play a key role in coping with the ongoing explosion in data-traffic demand and services. Compared to 4G MIMO technologies, massive MIMO can offer large gains in cell spectral efficiency, which, in combination with small cells and additional bandwidth, can translate into vast gains in throughput per unit area. We briefly overview the most promising TDD and FDD operation modes for massive MIMO, and discuss their potential benefits and challenges considering operation over different tiers and frequency bands. TDD operation is naturally suited to massive MIMO and can offer "massive MIMO" gains, with simple in-cell processing, low overheads and low end-to-end latencies. We also briefly describe some important massive MIMO activities towards 5G, including standardization efforts, system development and experimental trials.

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Section: Achievable Rates For Large But Finite Numbers Of Antennasmentioning

confidence: 64%

Massive MIMO Technologies and Challenges towards 5G

Papadopoulos¹,

Wang²,

Bursalioglu³

et al. 2016

IEICE Trans. Commun.

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“…When deriving the ESE, we can adopt the general power consumption model for each BS specified by the standards organizations [4]. Next we define the outage probability 4 for a typical No-CoMP UE u…”

Section: E Performance Metricsmentioning

confidence: 99%

“…] contains a factor of 4 Replacing (1) with the maximum possible received power P sb In L i j h i j , we have the capacity R max…”

Section: A Average DL Transmit Powers Of No-comp and Comp Uesmentioning

confidence: 99%

Joint Energy-Spectral-Efficiency Optimization of CoMP and BS Deployment in Dense Large-Scale Cellular Networks

Zhao

Chen

Zhao

et al. 2017

IEEE Trans. Wireless Commun.

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Abstract-In this paper, the energy-spectral efficiency (ESE) benefiting from the joint optimization of coordinated multipoint (CoMP) transmission and base station (BS) deployment are evaluated in the context of dense large-scale cellular network. We first derive a closed-form network ESE expression for a largescale CoMP-enhanced network, which allows us to quantify the influence of key network parameters on the achievable network ESE, including the BS density and the cooperation activation probability characterized by a CoMP activation factor as well as the users' behaviors, such as their geographical mobile-traffic intensity and average user rate. With the aid of this tractable ESE expression and for a given BS density, we next formulate a cellular-scenario-aware CoMP activation optimization problem whilst considering the users' outage probability as constraints to maximize the network's ESE. We then further jointly optimize the CoMP activation factor and the BS density to maximize the network ESE, again under the constraint of the users' outage probability. Our simulation results confirm the accuracy of our analysis and verify the impact of several key parameters on the network ESE. Finally, the ESE improvement of our proposed strategies is evaluated under diverse scenarios, which provides valuable insight into joint CoMP and BS deployment optimization in dense large-scale cellular networks.

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“…where R k,m,n denotes the achievable rate of k th user served by femtocell m on RB n. From equation (6), considering also (2) and (3), it can be observed that the FUEs sum rate is a function of both femtocell RB and power allocation policy, i.e. R = f (φ, p).…”

Section: Optimal Resource Allocation (Ora)mentioning

confidence: 99%

“…It is indicated in [2] that dense deployment of Femto Access Points (FAPs) 1 to Wi-Fi. However, these FAPs, serving indoor subscribers as part of the operators network, need to be operated in a licensed band.…”

Section: Introductionmentioning

confidence: 99%

Dynamic femtocell resource allocation for managing inter‐tier interference in downlink of heterogeneous networks

et al. 2016

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This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macrocells and femtocells sharing the same frequency band. The focus is to devise optimised policies for femtocells' access to the shared spectrum, in terms of femtocell transmissions, in order to maximise femto users sum data rate while ensuring that certain level of quality of service (QoS) for the macro-cell users in the vicinity of femtocells is provided. The optimal solution to this problem is obtained by employing the well-known Dual Lagrangian method and the optimal femtocell transmit power and resource allocation solution is derived in detail. However, the optimal solution introduces high computational complexity and may not be feasible to apply in real-time systems. To this end, we propose a heuristic solution to the problem. The algorithms to implement both optimal and efficient suboptimal schemes in a practical system are also given in detail while their complexity is compared. Simulation results show that our proposed dynamic resource allocation scheme a) ensures the macro users QoS requirements compared to the Reuse-1 scheme, where femtocells are allowed to transmit at full power and bandwidth; b) can maintain femto user data rates at high levels, compared to the Orthogonal Frequency Reuse scheme, where the network bandwidth resources are partially divided amongst macro and femtocells; and c) provides performance close to the optimal solution, while introducing much lower complexity.

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A holistic view on hyper-dense heterogeneous and small cell networks

Cited by 488 publications

References 9 publications

Massive MIMO Technologies and Challenges towards 5G

Massive MIMO Technologies and Challenges towards 5G

Joint Energy-Spectral-Efficiency Optimization of CoMP and BS Deployment in Dense Large-Scale Cellular Networks

Dynamic femtocell resource allocation for managing inter‐tier interference in downlink of heterogeneous networks

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