Downlink Scheduling and Resource Allocation for 5G MIMO-Multicarrier: OFDM vs FBMC/OQAM

Femenias, Guillem; Riera-Palou, Felip; Mestre, Xavier; Bonafé, Juan José Olmos

doi:10.1109/access.2017.2729599

Cited by 34 publications

(38 citation statements)

References 29 publications

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“…Note that the code-allocation order for the three cells does not affect the performance of the proposed algorithm. As shown in (22), the circled numbers denote the indices of code-allocation iterations, which will be explained in the following. The underlined numbers in the matrix indicate the allocation result, corresponding to the pairs of co-code users that are assigned the same code.…”

Section: Code Allocationmentioning

confidence: 99%

“…Against the background, we therefore motivate to investigate the resource allocation in the multicell downlink MC DS‐CDMA systems, both subcarrier and code allocation are addressed. Future wireless communications, such as 5G networks, will have more stringent QoS requirements and link reliability requirements than 4G ones and will feature innovative strategies . Hence, our resource allocation in the multicell MC DS‐CDMA systems are designed with the objective to maximize the system's reliability (or minimize the average error probability).…”

Section: Introductionmentioning

confidence: 99%

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High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

Shi

Xiao

Liang

et al. 2018

Trans Emerging Tel Tech

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In this paper, we investigate resource allocation in the multicarrier spread spectrum systems, especially in the multicell downlink multicarrier direct‐sequence code division multiple‐access systems. The allocation of resources including subcarriers and spreading codes aims to maximize the system reliability, thereby resulting in the high‐reliability mutlicarrier systems. For the sake of achieving low complexity, we develop the novel resource allocation framework. We propose two resource allocation algorithms, which are the simplified heuristic subcarrier‐ and code‐allocation (SHSC) algorithm and the enhanced heuristic subcarrier‐ and code‐allocation (EHSC) algorithm. The two proposed algorithms can find the promising suboptimum solutions to the mixed integer nonconvex resource allocation problem. The SHSC algorithm has lower complexity and demands less backhaul resources than the EHSC algorithm. In return, the EHSC algorithm performs better than the SHSC algorithm. Nevertheless, we show that both algorithms significantly outperform the existing algorithms while approaching the optimal algorithm of high complexity.

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Section: Code Allocationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

Shi

Xiao

Liang

et al. 2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…To address the challenges of 5G, Feminias et al [13] have recently proposed a novel cross-layer SRA framework by extending their previous work [14]. In their work, the utility function is defined in terms of the weighted goodput for cross-layer SRA.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we extend the performance evaluation to consider the eMTC and URLLC in addition to LTE. For LTE, our SRA algorithm outperforms the greedy approach [13] by up to 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness, conforming to [17]. For eMTC and URLLC associated with more demanding performance requirements, our SRA algorithm continues to outperform the greedy cross-layer approach [13] by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively.…”

mentioning

confidence: 98%

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Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems

Vora

Kang

2018

Technologies

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In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource Allocation (SRA) considering the channel and queue state, while supporting fairness. In this paper, we extend the SRA algorithm to consider 5G use-cases, namely enhanced Machine Type Communication (eMTC), Ultra-Reliable Low Latency Communication (URLLC) and enhanced Mobile BroadBand (eMBB). In a simulation study, we evaluate the performance of our SRA algorithm in comparison to an advanced greedy cross-layer algorithm for eMTC, URLLC and LTE (long-term evolution). For eMTC and URLLC, our SRA method outperforms the greedy approach by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively. In the case of LTE, our approach outperforms the greedy method by 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness compared with tested baseline.

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Multiuser Scheduling

Fuente

2020

Wiley 5G Ref

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Scheduling and resource allocation (SRA) strategies play a crucial role in the emerging fifth‐generation (5G) systems based on massive multiple‐input multiple‐output (MaMIMO) transmissions. The set of resources to allocate is increased, adding to the time, frequency, modulation, and coding resources, the spatial dimension introduced by MaMIMO. These spatial resources are provided by precoding schemes based on the channel state information knowledge at the transmitter side (CSIT). The joint optimization of all the input variables together with the quality of service (QoS) requirements established by the upper layers results in a complex cross‐layer optimization problem. Different metric criteria for SRA algorithms are studied in the literature. MaMIMO SRA is based on CSIT knowledge to select a feasible set of users to allocate the resources of a scheduling interval. This article provides a detailed view of the required mechanisms to understand the SRA process in the emerging 5G systems. To conclude this article, some challenging solutions regarding the utilization of heterogeneous scenarios, MaMIMO transmissions, millimeter wave (mmWave) frequencies, and artificial intelligence are presented.

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Downlink Scheduling and Resource Allocation for 5G MIMO-Multicarrier: OFDM vs FBMC/OQAM

Cited by 34 publications

References 29 publications

High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems

Multiuser Scheduling

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