A novel cross-layer resource allocation scheme for multi-user, multi-service, MIMO-OFDMA systems

Kambou, Samy; Perrine, Clency; Afif, Mériem; Pousset, Yannis; Olivier, Christian

doi:10.1109/pimrc.2015.7343458

Cited by 1 publication

(5 citation statements)

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“…Several recent works have begun to consider OFDMA and MU-MIMO together [ 12 , 13 , 14 , 15 , 20 , 21 ]. Femanias et al examine subcarrier and power allocation as well as stream selection for downlink networks [ 12 ].…”

Section: Related Workmentioning

confidence: 99%

“…Hamda et al optimize the transmit power in an uplink cooperative MU-MIMO/OFDMA network by taking into account optimal relay selection [ 13 ]. In addition, many resource allocation methods have been proposed for various purposes, for example user-fairness [ 20 ], QoS (Quality of Service) [ 21 ], and PSNR (Peak Signal-to-Noise Ratio) for video communications [ 14 ]. Similar to our work, the recent seminal work by Kordbacheh et al models the interaction from the physical data rate to routing in the optimization for MU-MIMO/OFDMA networks, but a different approach is employed: greedy algorithm development from nonlinear optimization formulation [ 15 ].…”

Section: Related Workmentioning

confidence: 99%

“…In addition, the heterogeneity of the nodes has not been sufficiently considered in these approaches; they are based on the assumption of equal available bandwidth [ 13 , 14 , 15 , 20 , 21 ] or the same number of antennas for the nodes [ 14 ], and in particular, the joint use of OFDMA and MU-MIMO is assumed to be always available at all the nodes [ 13 , 14 , 15 , 20 , 21 ]. Optimal resource allocation in MIMO/OFDMA heterogeneous networks in fact has attracted much attention, and various heterogeneity aspects have been investigated in recent studies.…”

Section: Related Workmentioning

confidence: 99%

“…First, a few studies have considered interactions between OFDMA [ 8 , 9 , 10 , 11 ] and MU-MIMO [ 3 , 4 , 5 , 6 , 7 ]; instead, most have focused on maximizing the performance of only one of these technologies. Several recent studies have addressed the joint use of these within optimization models, but have considered only single-hop networks [ 12 , 13 , 14 , 15 , 20 , 21 ]. In this network model, the effect of interference between nodes is relatively limited, which causes the network performance to be overestimated, and as a result, these approaches may not be applicable to various multi-hop network scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, even though the types and capabilities of network devices are becoming more diverse, this heterogeneity has not been sufficiently considered in relation to optimization; the same available bandwidth is assumed [ 13 , 14 , 15 , 20 , 21 ], or even the same number of antennas of nodes [ 14 ], and in particular, the joint use of OFDMA and MU-MIMO is generally assumed to be always available at all the nodes [ 13 , 14 , 15 , 20 , 21 ]. These assumptions may have the advantage of simplifying the model, but they are somewhat different from the conditions in actual networks; for example, although OFDMA has now been introduced to Wi-Fi systems through IEEE 802.11ax [ 1 ], the joint use of MU-MIMO and OFDMA is not allowed, and most legacy devices, including IoT (Internet of Things) products, are unable to operate with a wide band of 160 MHz and large number of antennas, due to the form factor and the processing power required.…”

Section: Introductionmentioning

confidence: 99%

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Cross-Layer Optimization for Heterogeneous MU-MIMO/OFDMA Networks

Lee

Kim

2021

Sensors

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To enable the full benefits from MU-MIMO (Multiuser-Multiple Input Multiple Output) and OFDMA (Orthogonal Frequency Division Multiple Access) to be achieved, the optimal use of these two technologies for a given set of network resources has been investigated in a rich body of literature. However, most of these studies have focused either on maximizing the performance of only one of these schemes, or have considered both but only for single-hop networks, in which the effect of the interference between nodes is relatively limited, thus causing the network performance to be overestimated. In addition, the heterogeneity of the nodes has not been sufficiently considered, and in particular, the joint use of OFDMA and MU-MIMO has been assumed to be always available at all nodes. In this paper, we propose a cross-layer optimization framework that considers both OFDMA and MU-MIMO for heterogeneous wireless networks. Not only does our model assume that the nodes have different capabilities, in terms of bandwidth and the number of antennas, but it also supports practical use cases in which nodes can support either OFDMA or MU-MIMO, or both at the same time. Our optimization model carefully takes into account the interactions between the key elements of the physical layer to the network layer. In addition, we consider multi-hop networks, and capture the complicated interference relationships between nodes as well as multi-path routing via multi-user transmissions. We formulate the proposed model as a Mixed Integer Linear Programming (MILP) problem, and initially model the case in which each node can selectively use either OFDMA or MU-MIMO; we then extend this to scenarios in which they are jointly used. As a case study, we apply the proposed model to sum-rate maximization and max–min fair allocation, and verify through MATLAB numerical evaluations that it can take appropriate advantage of each technology for a given set of network resources. Based on the optimization results, we also observe that when the two technologies are jointly used, more multi-user transmissions are enabled thanks to flexible resource allocation, meaning that greater use of the link capacity is achieved.

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