Small cell backhaul: challenges and prospective solutions

Jafari, Amir; López-Pérez, David; Song, Hui; Claußen, Holger; Ho, Lester; Zhang, Jie

doi:10.1186/s13638-015-0426-y

Cited by 60 publications

(21 citation statements)

References 34 publications

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“…, K} connects to a backhaul link with limited capacity. The backhaul link of each BS carries the downlink traffic for its serviced UEs from the core network to that BS via a central access point called 'Point of Presence' (PoP) [17], [27], [28]. The PoP is connected to the core network via an optical fiber link whose capacity is much higher than the total capacity of all links from the PoP to all BSs.…”

Section: System Model and Problem Formulationsmentioning

confidence: 99%

“…In Step 3, we solve convex problem (27) instead of (14). In Step 4, we solve convex problem (29) instead of (22).…”

Section: Proposed Alternating Descent Algorithm For Minimum Ue Ramentioning

confidence: 99%

“…In each iteration of Algorithm 2, the computational complexity of solving problem (27) is (27) can be equivalently reformulated as an optimization problem with a = (N K + 1) scalar real decision variables, a linear objective, c (N + K) linear constraints and N quadratic constraints [37]. Similarly, the complexity of solving problem (29) is of linear matrix inequalities.…”

Section: Proposed Alternating Descent Algorithm For Minimum Ue Ramentioning

confidence: 99%

See 2 more Smart Citations

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Tam

Tuan

Ngo

et al. 2017

IEEE Trans. Wireless Commun.

110

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Abstract-In this paper, new strategies are devised for joint load balancing and interference management in the downlink of a heterogeneous network, where small cells are densely deployed within the coverage area of a traditional macrocell. Unlike existing work, the limited backhaul capacity at each base station (BS) is taken into account. Here users (UEs) cannot be offloaded to any arbitrary BS, but only to ones with sufficient backhaul capacity remaining. Jointly designed with traffic offload, transmit power allocation mitigates the intercell interference to further support the quality of service of each UE. The objective here is either (i) to maximize the network sum rate subject to minimum throughput requirements at individual UEs, or (ii) to maximize the minimum UE throughput. Both formulated problems belong to the difficult class of mixed-integer nonconvex optimization. The inherently binary BS-UE association variables are strongly coupled with the transmit power variables, making the problems even more challenging to solve. New iterative algorithms are developed based on an exact penalty method combined with successive convex programming, where we deal with the binary BS-UE association problem and the nonconvex power allocation problem one at a time. At each iteration of the proposed algorithms, only two simple convex problems need to be solved in the same time scale. It is proven that the algorithms improve the objective functions in each iteration and converge eventually. Numerical results demonstrate the efficiency of the proposed algorithms in both traffic offloading and interference mitigation.

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Section: System Model and Problem Formulationsmentioning

confidence: 99%

“…In Step 3, we solve convex problem (27) instead of (14). In Step 4, we solve convex problem (29) instead of (22).…”

Section: Proposed Alternating Descent Algorithm For Minimum Ue Ramentioning

confidence: 99%

Section: Proposed Alternating Descent Algorithm For Minimum Ue Ramentioning

confidence: 99%

See 1 more Smart Citation

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Tam

Tuan

Ngo

et al. 2017

IEEE Trans. Wireless Commun.

110

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“…More than 40,000 small cells were deployed in 2015 [65], and this number is expected to increase in the future upon the deployment of 5G technology [66]. As shown in [67], the number of 5G small cells is anticipated to become four times larger than the number of existing macro sites to cover the same service area.…”

Section: Network Planning and Deploymentmentioning

confidence: 99%

Green and Sustainable Cellular Base Stations: An Overview and Future Research Directions

Alsharif

Kim

2017

Energies

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Energy efficiency and renewable energy are the main pillars of sustainability and environmental compatibility. This study presents an overview of sustainable and green cellular base stations (BSs), which account for most of the energy consumed in cellular networks. We review the architecture of the BS and the power consumption model, and then summarize the trends in green cellular network research over the past decade. As its major contribution, this study highlights the uses of renewable energy in cellular communication by: (i) investigating the system model and the potential of renewable energy solutions for cellular BSs; (ii) identifying the potential geographical locations for renewable-energy-powered BSs; (iii) performing case studies on renewable-energy-powered cellular BSs and suggesting future research directions based on our findings; (iv) examining the present deployment of sustainable and green BSs; and (v) studying the barriers that prevent the widespread use of renewable-energy-powered BSs and providing recommendations for future work.

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“…In fact, Dandelion codes have been shown to possess better locality and heritability characteristics than any other Cayley codes when undergoing different evolutionary operators [20,21]. This superior performance of Dandelion codes has unleashed a flurry of research gravitating on their application in different scenarios and sectors, such as Telecommunications [22] and Energy [23].…”

Section: Solution Encodingmentioning

confidence: 99%

Joint Topology Optimization, Power Control and Spectrum Allocation for Intra-Vehicular Multi-hop Sensor Networks Using Dandelion-Encoded Heuristics

Ser

Bilbao

Perfecto

et al. 2016

Applications of Evolutionary Computation

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Abstract. In the last years the interest in multi-hop communications has gained momentum within the research community due to the challenging characteristics of the intra-vehicular radio environment and the stringent robustness imposed on critical sensors within the vehicle. As opposed to point-to-point network topologies, multi-hop networking allows for an enhanced communication reliability at the cost of an additional processing overhead. In this context this manuscript poses a novel bi-objective optimization problem aimed at jointly minimizing 1) the average Bit Error Rate (BER) of sensing nodes under a majority fusion rule at the central data collection unit; and 2) the mean delay experienced by packets forwarded by such nodes due to multi-hop networking, frequency channel switching time multiplexing at intermediate nodes.The formulated paradigm is shown to be computationally tractable via a combination of evolutionary meta-heuristic algorithms and Dandelion codes, the latter capable of representing tree-like structures like those modeling the multi-hop routing approach. Simulations are carried out for realistic values of intra-vehicular radio channels and co-channel interference due to nearby IEEE 802.11 signals. The obtained results are promising and pave the way towards assessing the practical performance of the proposed scheme in real setups.

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Small cell backhaul: challenges and prospective solutions

Cited by 60 publications

References 34 publications

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Green and Sustainable Cellular Base Stations: An Overview and Future Research Directions

Joint Topology Optimization, Power Control and Spectrum Allocation for Intra-Vehicular Multi-hop Sensor Networks Using Dandelion-Encoded Heuristics

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