Optimal power allocation for multiple-input-multiple-output relaying system

Zhang, Jingmei; Chunju, Shao; Wang, Ying; Zhang, Ping

doi:10.1109/vetecf.2004.1400255

Cited by 13 publications

(3 citation statements)

References 7 publications

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“…Due to the flexible deployment and low cost, unmanned aerial vehicle (UAV) is widely used in data backhaul transmission, especially as a kind of relay device to enhance the capacity and spectrum utilization of radio access networks (RANs) [1]- [6]. However, with the explosive increase of user number, the volume of data traffic in RANs has grown exponentially and the traffic types have become more diverse.…”

Section: Introductionmentioning

confidence: 99%

UAV-Enabled Multiple Traffic Backhaul Based on Multiple RANs: A Batch-Arrival-Queuing-Inspired Approach

Zhi

et al. 2019

IEEE Access

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In this paper, we investigate the air-to-ground multi-traffic backhaul enabled by unmanned aerial vehicle (UAV) equipped with multiple radio access networks (RANs). Faced with the challenging traffic designation problem over diverse RANs, an efficient packet delivery scheme based on multi-priority batch arrival queuing theory is proposed to match various traffics with multiple RANs. Specifically, our contributions are threefold: 1) The average queuing time of UAV-enabled multi-RAN access is theoretically derived according to multi-priority batch arrival queuing theory. 2) The priority factor and z-type utility function are well tailored by leveraging the derived queuing time. 3) A multiple traffic backhaul strategy is further proposed by exploiting the priority factor and z-type utility function to optimize the packet delivery, i.e., maximizing the delay utility via joint network selection and power allocation for diverse RANs. The simulation results show that the average delay of delay-sensitive packets is reduced by 15%, and the overall packet delivery quality is improved considerably. INDEX TERMS Unmanned aerial vehicle (UAV), resource allocation, queuing theory, multi-priority, traffic backhaul.

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Section: Introductionmentioning

confidence: 99%

UAV-Enabled Multiple Traffic Backhaul Based on Multiple RANs: A Batch-Arrival-Queuing-Inspired Approach

Zhi

et al. 2019

IEEE Access

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“…In [10], the authors investigated power allocation for a two-hop decode-and-forward relaying system assuming full CSI availability at the source while the relay has either partial or full CSI. The case of amplify-and-forward relaying under similar assumptions for single-antenna and multiple-antenna configurations at the source node are studied in [11] and [12], respectively. Finally, the authors in [13] studied power allocation schemes in a multi-cell environment where both decode-and-forward or amplify-and-forward are considered for the relaying.…”

Section: Introductionmentioning

confidence: 99%

Joint optimization of power allocation and relay position for regenerative relaying in the presence of co-channel interference

Ikki

Aı̈ssa

2011

2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications

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We consider power allocation and relay positioning with the objective to minimize system error probability in a dualhop regenerative relaying system operating under co-channel interference. First, assuming fixed relay location, adaptive power allocation at the source and the relay nodes under joint power constraint is presented. Then considering fixed power allocation scheme, the optimal relay position is obtained. Results show that optimum power allocation, optimum relay location and joint optimization of the power allocation and relay positioning significantly improve the system performance in terms of error probability compared to uniform power allocation and mid-point distance location for the relay node.

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“…In [9], the authors have investigated power allocation for a twohop DaF relaying system assuming full CSI availability at the source while the relay has either full or partial CSI. The case of AaF relaying under similar assumptions is studied in [10] and extended in [11] for source terminal with multiple antennas. Finally, in [12], power allocation schemes have been studied in a multi-cell environment where both DaF or AaF relaying are considered.…”

Section: Introductionmentioning

confidence: 99%

Joint Optimization of Power Allocation and Relay Location for Decode-and-Forward Dual-Hop Systems over Nakagami-m Fading Channels

Ikki

Uysal

Ahmed

2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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We consider power allocation (PA) and relay positioning in a dual-hop decode-and-forward relaying system over Nakagami-m fading channels. We investigate adaptive power allocation (PA) with fixed relay location, optimal relay location with fixed power allocation and joint optimization of the PA and relay location under transmit power constraint in order to minimize outage probability and average error probability upper bound. Results show that the analyzed adaptive algorithms outperform uniform algorithms and direct transmission. It is also found that as the source destination channel is getting better, the less power will be needed to allocate to the relay node in order to satisfy the optimization criteria. Numerical results are presented to verify our analysis 1 .

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Optimal power allocation for multiple-input-multiple-output relaying system

Cited by 13 publications

References 7 publications

UAV-Enabled Multiple Traffic Backhaul Based on Multiple RANs: A Batch-Arrival-Queuing-Inspired Approach

UAV-Enabled Multiple Traffic Backhaul Based on Multiple RANs: A Batch-Arrival-Queuing-Inspired Approach

Joint optimization of power allocation and relay position for regenerative relaying in the presence of co-channel interference

Joint Optimization of Power Allocation and Relay Location for Decode-and-Forward Dual-Hop Systems over Nakagami-m Fading Channels

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