Statistical-QoS Driven Energy-Efficiency Optimization Over Green 5G Mobile Wireless Networks

Cheng, Wenchi; Zhang, Xi; Zhang, Hailin

doi:10.1109/jsac.2016.2599980

Cited by 94 publications

(59 citation statements)

References 29 publications

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“…A constraint optimization problem that can maximize the cellular users EC has been formulated. This study reveals that as the arrival rate [175] VoIP Application [41] 2D Applications [22] Multi-User QoS Provisioning [21] Downlink Scheduling of Real-Time Traffic [23] QoS Provisioning In Cellular D2D Communications [168] Support for Real-Time Applications in Heterogeneous Cells [282] QoS-Provisioning in Visible Light supportive Cellular Networks [28] Video Streaming [63] Energy-Efficient Based QoS Provisioning [189], [283] QoS-Provisioning In OFDMA-Based Femto-Cells [185] QoS-Provisioning In Two-Tier Femto-Cells [171], [179], [186], [284] Video Streaming [58], [61] Uplink QoS Provisioning [106] Energy-Efficient QoS Provisioning In Green 5G Networks [108] QoS-Provisioning in Full-Duplex 5G Networks [113] of D2D pairs increases, the EC decreases and interference to the BS increases. This framework is then used to develop an adaptive power allocation scheme.…”

Section: Cellular Networkmentioning

confidence: 99%

Effective Capacity in Wireless Networks: A Comprehensive Survey

Amjad

Musavian

Rehmani

2019

IEEE Commun. Surv. Tutorials

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Low latency applications, such as multimedia communications, autonomous vehicles, and Tactile Internet are the emerging applications for next-generation wireless networks, such as 5th generation (5G) mobile networks. Existing physicallayer channel models, however, do not explicitly consider qualityof-service (QoS) aware related parameters under specific delay constraints. To investigate the performance of low-latency applications in future networks, a new mathematical framework is needed. Effective capacity (EC), which is a link-layer channel model with QoS-awareness, can be used to investigate the performance of wireless networks under certain statistical delay constraints. In this paper, we provide a comprehensive survey on existing works, that use the EC model in various wireless networks. We summarize the work related to EC for different networks such as cognitive radio networks (CRNs), cellular networks, relay networks, adhoc networks, and mesh networks. We explore five case studies encompassing EC operation with different design and architectural requirements. We survey various delay-sensitive applications such as voice and video with their EC analysis under certain delay constraints. We finally present the future research directions with open issues covering EC maximization.

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Section: Cellular Networkmentioning

confidence: 99%

Effective Capacity in Wireless Networks: A Comprehensive Survey

Amjad

Musavian

Rehmani

2019

IEEE Commun. Surv. Tutorials

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“…Next, we compare our algorithm to the following existing algorithms in terms of the achievable effective capacity: 1) Nearest RRH serving algorithm: As the terminology suggests, this algorithm assigns the nearest RRH to serve the user and the algorithm developed in [12] for simple point-to-point systems is used for solving the power allocation problem. This algorithm is provided to show the gains gleaned from cooperative transmission in CRANs.…”

Section: A Single-user Casementioning

confidence: 99%

Low-Latency C-RAN: An Next-Generation Wireless Approach

Ren

Liu

Pan

et al. 2018

IEEE Veh. Technol. Mag.

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Abstract-Cloud radio access networking (C-RAN) constitutes a promising architecture for next-generation systems. Beneficial centralized signal processing techniques can be realized under the C-RAN architecture. Furthermore, given the recent rapid development of cloud computing, the C-RAN architecture is an ideal platform for supporting network function virtualization (NFV), software-defined networking (SDN) and artificial intelligence (AI). However, most of the existing contributions on C-RAN are mainly focused on the physical layer issues. The nextgeneration networks are expected to support compelling wireless applications satisfying diverse delay requirements, such as ultrareliable and low-latency communications (URLLC), etc. Hence, we invoke the effective capacity theory for statistical delaybounded QoS provision in C-RAN architectures, where the delay is taken into account. Based on the system model proposed, we conceive sophisticated power allocation schemes for maximizing the effective capacity of both single-user and multi-user scenarios. Our simulation results show that a low delay outage probability can be guaranteed by appropriately choosing the delay exponent. Furthermore, our simulation results demonstrate that the proposed algorithm significantly outperforms the existing algorithms in terms of the achievable effective capacity. Finally, some open research challenges are highlighted.

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“…Due to the complex expression of EC, most of the existing papers focus on the EC maximization problem for the simple scenario, where there is only a single transmitter [7]- [11]. Specifically, a QoS-driven power-and rate-adaptation scheme was proposed for single-input single-output (SISO) systems communicating over flat-fading channels in [7], with the objective of maximizing EC subject to both delay-QoS and average power constraints, which is characterized by the QoS exponent θ.…”

Section: Introductionmentioning

confidence: 99%

Power- and Rate-Adaptation Improves the Effective Capacity of C-RAN for Nakagami-$m$ Fading Channels

Ren

Liu

Pan

et al. 2018

IEEE Trans. Veh. Technol.

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We propose a power-and rate-adaptation scheme for cloud radio access networks (C-RANs), where each radio remote head (RRH) is connected to the baseband unit (BBU) pool through optical links. The RRHs jointly support the users by efficiently exploiting the enhanced spatial degrees of freedom. Our proposed scheme aims for maximizing the effective capacity (EC) of the user subject to both per-RRH average-and peak-power constraints, where the EC is defined as the maximum arrival rate that can be supported by the C-RAN under the statistical delay requirement. We first transform the EC maximization problem into an equivalent convex optimization problem. By using the Lagrange dual decomposition method and solving the Karush-Kuhn-Tucker (KKT) equations, the optimal transmission power of each RRH can be obtained in closed-form. Furthermore, an online tracking method is provided for approximating the average power of each RRH. For the special case of two RRHs, the expression of the average power of each RRH can be calculated in explicit form. Hence, the Lagrange dual variables can be computed in advance in this special case. Furthermore, we derive the power allocation for two important extreme cases: 1) no delay constraint; 2) extremely stringent delay-requirements. Our simulation results show that the proposed scheme significantly outperforms the conventional algorithm without considering the delay requirements. Furthermore, when appropriately tuning the value of the delay exponent, our proposed algorithm is capable of guaranteeing a delay outage probability below 10 −9 when the maximum tolerable delay is 1 ms. This is suitable for the future ultra-reliable low latency communications (URLLC).

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Statistical-QoS Driven Energy-Efficiency Optimization Over Green 5G Mobile Wireless Networks

Cited by 94 publications

References 29 publications

Effective Capacity in Wireless Networks: A Comprehensive Survey

Effective Capacity in Wireless Networks: A Comprehensive Survey

Low-Latency C-RAN: An Next-Generation Wireless Approach

Power- and Rate-Adaptation Improves the Effective Capacity of C-RAN for Nakagami-$m$ Fading Channels

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