Massive MIMO Optimization With Compatible Sets

Fitzgerald, Emma; Pióro, Michał; Tufvesson, Fredrik

doi:10.1109/twc.2019.2908362

Cited by 9 publications

(7 citation statements)

References 55 publications

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“…This property can have a significant impact on the inter-node interference in massive MIMO networks, particularly when simple maximum ratio combining (MRC) is used for precoding [3]. Furthermore, the average received power can be effectively used for node grouping and scheduling [4]. Nevertheless, inter-node interference can also be strongly affected by the directional properties of the users' channels.…”

Section: Motivationmentioning

confidence: 99%

A Light Signaling Approach to Node Grouping for Massive MIMO IoT Networks

et al. 2022

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Massive MIMO is one of the leading technologies for connecting very large numbers of energy-constrained nodes, as it offers both extensive spatial multiplexing and large array gain. A challenge resides in partitioning the many nodes into groups that can communicate simultaneously such that the mutual interference is minimized. Here we propose node partitioning strategies that do not require full channel state information, but rather are based on nodes’ respective directional channel properties. In our considered scenarios, these typically have a time constant that is far larger than the coherence time of the channel. We developed both an optimal and an approximation algorithm to partition users based on directional channel properties, and evaluated them numerically. Our results show that both algorithms, despite using only these directional channel properties, achieve similar performance in terms of the minimum signal-to-interference-plus-noise ratio for any user, compared with a reference method using full channel knowledge. In particular, we demonstrate that grouping nodes with related directional properties is to be avoided. We hence realize a simple partitioning method, requiring minimal information to be collected from the nodes, and in which this information typically remains stable over the long term, thus promoting the system’s autonomy and energy efficiency.

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Section: Motivationmentioning

confidence: 99%

A Light Signaling Approach to Node Grouping for Massive MIMO IoT Networks

et al. 2022

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“…This property can have a significant impact on the inter-node interference in massive MIMO, particularly when simple maximum ratio combining (MRC) is used for precoding [2]. Furthermore, the average received power can be effectively used for node grouping and scheduling [3]. Nevertheless, inter-node interference can also be strongly affected by the directional properties of the users' channels.…”

Section: Motivationmentioning

confidence: 99%

“…Because massive MIMO systems serve multiple nodes simultaneously, such scheduling inherently requires creating node groups, although the groups do not necessarily need to be disjoint. In [3], joint node scheduling and transmission power control is performed for nodes with heterogeneous traffic demands. However, here, information about the traffic queues at each node is required, which increases the signalling needed and thus the energy cost.…”

Section: B Node Scheduling and Random Access For Massive Mimomentioning

confidence: 99%

A Light Signalling Approach to Node Grouping for Massive MIMO IoT Networks

Fitzgerald¹,

Pióro²,

Tataria³

et al. 2020

Preprint

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Massive MIMO is a promising technology to connect very large numbers of energy constrained nodes, as it offers both extensive spatial multiplexing and large array gain. A challenge resides in partitioning the many nodes in groups that can communicate simultaneously such that the mutual interference is minimized. We here propose node partitioning strategies that do not require full channel state information, but rather are based on nodes' respective directional channel properties. In our considered scenarios, these typically have a time constant that is far larger than the coherence time of the channel. We developed both an optimal and an approximation algorithm to partition users based on directional channel properties, and evaluated them numerically. Our results show that both algorithms, despite using only these directional channel properties, achieve similar performance in terms of the minimum signal-to-interferenceplus-noise ratio for any user, compared with a reference method using full channel knowledge. In particular, we demonstrate that grouping nodes with related directional properties is to be avoided. We hence realise a simple partitioning method requiring minimal information to be collected from the nodes, and where this information typically remains stable over a long term, thus promoting their autonomy and energy efficiency.

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“…• Scalable and adaptive resource allocation. A important insight from studies of massive MIMO [25] is that power control and allocation is crucial to avoid near-far effects and thereby achieve consistent good quality of service. This insight is key for scheduling users and allocating resources in the new RadioWeaves.…”

Section: Randd Challenges and Opportunitiesmentioning

confidence: 99%

RadioWeaves for efficient connectivity: analysis and impact of constraints in actual deployments

Perre

Larsson

Tufvesson

et al. 2019

2019 53rd Asilomar Conference on Signals, Systems, and Computers

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We present a new type of wireless access infrastructure consisting of a fabric of dispersed electronic circuits and antennas that collectively function as a massive, distributed antenna array. We have chosen to name this new wireless infrastructure "RadioWeaves" and anticipate they can be integrated into indoor and outdoor walls, furniture, and other objects, rendering them a natural part of the environment. Technologically, RadioWeaves will deploy distributed arrays to create both favorable propagation and antenna array interaction. The technology leverages on the ideas of large-scale intelligent surfaces and cell-free wireless access. Offering close to the service connectivity and computing, new grades in energy efficiency, reliability, and low latency can be reached. The new concept moreover can be scaled up easily to offer a very high capacity in specific areas demanding so. In this paper we anticipate how two different demanding use cases can be served well by a dedicated RadioWeaves deployment: a crowd scenario and a highly reflective factory environment. A practical approach towards a RadioWeaves prototype, integrating dispersed electronics invisibly in a room environment, is introduced. We outline the many and diverse R&D challenges that need to be addressed to realize the great potential of the RadioWeaves technology. Index Terms-RadioWaves, energy efficient and ultra reliable connectivity, large-scale antenna arrays, cell-free wireless access. L. Van der Perre and L. De Strycker are with the Department of Electrical Engineering, KU Leuven, Belgium; L. Van der Perre, F. Tufvesson, and O. Edfors are with the

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Massive MIMO Optimization With Compatible Sets

Cited by 9 publications

References 55 publications

A Light Signaling Approach to Node Grouping for Massive MIMO IoT Networks

A Light Signaling Approach to Node Grouping for Massive MIMO IoT Networks

A Light Signalling Approach to Node Grouping for Massive MIMO IoT Networks

RadioWeaves for efficient connectivity: analysis and impact of constraints in actual deployments

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