Analysis and Optimization of Inter-Tier Interference Coordination in Downlink Multi-Antenna HetNets With Offloading

Wu, Yueping; Cui, Ying; Clerckx, Bruno

doi:10.1109/twc.2015.2456174

Cited by 27 publications

(28 citation statements)

References 31 publications

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“…Corollary 2. The C K with full channel inversion (η = 1) is given by (12) while the L I (s) simplifies to (15), available at the top of this page, where s = τ K while the rest of the parameters remain the same. Corollary 3.…”

Section: B Special Casesmentioning

confidence: 99%

Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks With Multi- Antenna Base Stations

Bacha

Clerckx

2017

IEEE Trans. Wireless Commun.

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Abstract-In order to improve the uplink performance of future cellular networks, the idea to decouple the downlink (DL) and uplink (UL) association has recently been shown to provide significant gain in terms of both coverage and rate performance. However, all the work is limited to SISO network. Therefore, to study the gain provided by the DL and UL decoupling in multi-antenna base stations (BSs) setup, we study a two tier heterogeneous network consisting of multi-antenna BSs, and single antenna user equipments (UEs). We use maximal ratio combining (MRC) as a linear receiver at the BSs and using tools from stochastic geometry, we derive tractable expressions for both signal to interference ratio (SIR) coverage probability and rate coverage probability. We observe that as the disparity in the beamforming gain of both tiers increases, the gain in term of SIR coverage probability provided by the decoupled association over non-decoupled association decreases. We further observe that when there is asymmetry in the number of antennas of both tier, then we need further biasing towards femto-tier on the top of decoupled association to balance the load and get optimal rate coverage probability.

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Section: B Special Casesmentioning

confidence: 99%

Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks With Multi- Antenna Base Stations

Bacha

Clerckx

2017

IEEE Trans. Wireless Commun.

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“…Pr (u 0 ∈ U j ) (j = 1, 2) are given in (9) and (10). Here,L (n) (13) and (14) (with J(1O) = 1 and J(2) = 2), respectively. Moreover,…”

Section: Theorem 1 (Coverage Probability)mentioning

confidence: 99%

User-Centric Interference Nulling in Downlink Multi-Antenna Heterogeneous Networks

Cui

Jiang

et al. 2016

IEEE Trans. Wireless Commun.

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In heterogeneous networks (HetNets), strong interference due to spectrum reuse affects each user's signal-to-interference ratio (SIR), and hence is one limiting factor of network performance. In this paper, we propose a user-centric interference nulling (IN) scheme in a downlink large-scale HetNet to improve we first obtain a tractable expression of the coverage (equivalently outage) probability. Then, we analyze the asymptotic coverage/outage probability in the low and high SIR threshold regimes. The analytical results indicate that the maximum IN DoF can affect the order gain of the outage probability in the low SIR threshold regime, but cannot affect the order gain of the coverage probability in the high SIR threshold regime. Moreover, we characterize the optimal maximum IN DoF which optimizes the asymptotic coverage/outage probability. The optimization results reveal that the IN scheme can linearly improve the outage probability in the low SIR threshold regime, but cannot improve the coverage probability in the high SIR threshold regime. Finally, numerical results show that the proposed scheme can achieve good gains in coverage/outage probability over a maximum ratio beamforming scheme and a user-centric almost blank subframes (ABS) scheme.

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“…In [23], authors considered the single antenna systems at base stations. The works [30][31][32][33] focused on the asymptotic performance of conventional MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

“…While the aforementioned works [30][31][32][33] focused on the traditional MIMO systems, the works [34][35][36][37][38] contributed to the performance analysis of massive MIMO systems by employing stochastic geometry. Specially, in [34,35], the capacity and energy-efficiency of massive MIMO systems have been investigated.…”

Section: Introductionmentioning

confidence: 99%

“…Stochastic geometry is a powerful mathematical and statistical tool to model, analyze and design wireless networks with random topologies. Due to the fact that, in massive MIMO systems, the uplink/downlink performance is completely determined by shadow fading coefficients, and the effort of small-scale fading is averaged out entirely; the prior results for traditional MIMO in [30][31][32][33] do not directly apply to analyze uplink/downlink massive MIMO networks. Although the works [37][38][39][40] performed the analysis for massive MIMO systems by using stochastic geometric, they focused on single tier networks.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic geometry based asymptotic analysis for two‐tier HetNets with massive MIMO relay employing MRC/MRT and ZF processing

Jia

Zhou

Yang

et al. 2016

Trans. Emerging Tel. Tech.

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This paper focuses on the multi‐pair amplify‐and‐forward massive multiple‐input multiple‐output (MIMO) relay enabled two‐tier heterogeneous cellular networks in terms of aggregate spectral efficiency (SE), where the macro cells are overlaid with dense small cells. Specially, the maximum ratio combining/maximal ratio transmission and zero‐forcing processing schemes are employed at massive MIMO relay, respectively. The macro base stations located in the center of the cells are equipped with massive MIMO antenna array, while the randomly distributed macro users (MUs), small cell base stations, and small cell users are equipped with single antenna. The positions of MUs, small cell users and small cell base stations are modelled as independent Poisson point processes. For such two‐tier heterogeneous cellular networks, to obtain the aggregate SE in target cell, we first formulate the end‐to‐end signal‐to‐interference noise ratios for a communication pair as well as the expression of power amplification factor at target macro base stations so that the total spectrum efficiency per cell is formulated. Then, by employing stochastic geometry, the closed‐form expressions of the power amplification factor and the expectation of the reciprocal of the equivalent end‐to‐end signal‐to‐interference noise ratios are achieved. With these results, we derive the lower bounds of SEs for maximum ratio combining/maximal ratio transmission and zero‐forcing schemes. The derivations display a clear perspective about the impact of network parameters on the system‐level performance, which includes macro cell radius, small cell radius, macro cell guard radius, the mean number of MUs per cell and so on. To achieve optimal (or suboptimal) system performance, we find that the radius of small cell should be less than the guard radius. For the guard radius, there exists an upper bound, only under which the increase of the guard radius would contribute to the improvement of SE. At the same time, our results show that with given network parameters, especially the guard radius and the small cell radius, there exists a unique greatest lower bound in terms of macro cell radius. When the macro cell radius is less than the greatest lower bound, the aggregate SE is increasing with the macro cell radius. On the contrary, the achievable aggregate SE saturates to the corresponding constant, approximately. In addition, the greatest lower bound of the macro cell radius is the function of the guard radius and the small cell radius. Copyright © 2016 John Wiley & Sons, Ltd.

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Analysis and Optimization of Inter-Tier Interference Coordination in Downlink Multi-Antenna HetNets With Offloading

Cited by 27 publications

References 31 publications

Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks With Multi- Antenna Base Stations

Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks With Multi- Antenna Base Stations

User-Centric Interference Nulling in Downlink Multi-Antenna Heterogeneous Networks

Stochastic geometry based asymptotic analysis for two‐tier HetNets with massive MIMO relay employing MRC/MRT and ZF processing

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