Random access heterogeneous MIMO networks

Lin, Kate Ching-Ju; GollakotaShyamnath,; KatabiDina,

doi:10.1145/2043164.2018454

Cited by 51 publications

(24 citation statements)

References 23 publications

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“…More practically oriented work includes [2]. In [2] it is shown that in a Multi-Input Multi-Output (MIMO) network where nodes have up to t antennas, t concurrent transmissions can occur.…”

Section: Related Workmentioning

confidence: 99%

“…In [2] it is shown that in a Multi-Input Multi-Output (MIMO) network where nodes have up to t antennas, t concurrent transmissions can occur. Global state information is needed to this, which is included in RTS-CTS packets and are overheard.…”

Section: Related Workmentioning

confidence: 99%

“…Considering [2], it is unlikely that channel states of n transmitters can be kept updated for large n, especially if some temporal change in the state is to be expected.…”

Section: Related Workmentioning

confidence: 99%

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Maximum MIMO Flow in wireless networks under the SINR model

Ásgeirsson

Halldórsson

Mitra

2014

2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

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We present a framework for the maximum flow problem in wireless networks using the SINR interference model in combination with MIMO nodes. The performance ratio of our algorithm matches the best O(log n) approximation factor known for the pure flow problem, but avoids the impractical dependence on the ellipsoid method and features both simpler and more intuitive analysis.The objective of a maximum flow in wireless networks is to get as much information from a sender to a receiver using intermediate nodes in a multi-hop environment. The algorithm is based on an LP formulation of the flow problem, and handles gracefully all additional linear constraints. The set of constraints that can be included contains, among other, power limits, fairness between source-sink pairs, capacity limits and bounds, and the use of Multi-Input Multi-Output nodes for the source and the sink nodes, which are often the bottlenecks in a wireless flow.

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“…More practically oriented work includes [2]. In [2] it is shown that in a Multi-Input Multi-Output (MIMO) network where nodes have up to t antennas, t concurrent transmissions can occur.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Maximum MIMO Flow in wireless networks under the SINR model

Ásgeirsson

Halldórsson

Mitra

2014

2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

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“…Therefore, in [15] an alternative based on interference alignment and cancellation is proposed. Other streams of work related to spatial multiplexing in wireless systems have considered the use of directional antennas to limit interference [19], the use of additional antennas to transmit concurrently with other nodes without harming the ongoing transmissions [18], and applying multiuser detection techniques to the WiFi uplink [28].…”

Section: Related Work With Software Radio Testbedsmentioning

confidence: 99%

Achieving high data rates in a distributed MIMO system

Bălan

Rogalin

Michaloliakos

et al. 2012

Proceedings of the 18th Annual International Conference on Mobile Computing and Networking

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A distributed MIMO system consists of several access points connected to a central server and operating as a large distributed multi-antenna access point. In theory, such a system enjoys all the significant performance gains of a traditional MIMO system, and it may be deployed in an enterprise WiFi like setup. In this paper, we investigate the efficiency of such a system in practice. Specifically, we build upon our prior work on developing a distributed MIMO testbed, and study the performance of such a system when both full channel state information is available to the transmitters and when no channel state information is available.In the full channel state information scenario, we implement Zero-Forcing Beamforming (ZFBF) and TomlinsonHarashima Precoding (THP) which is provably near-optimal in high SNR conditions. In the scenario where no channel information is available, we implement Blind Interference Alignment (BIA), which achieves a higher multiplexing gain (degrees of freedom) than conventional TDMA. Our experimental results show that the performance of our implementation is very close to the theoretically predicted performance and offers significant gains over optimal TDMA. We also discuss medium access layer issues in detail for both scenarios. To the best of our knowledge, this is the first time that the theoretical high data rates of multiuser MIMO systems have been showcased in a real world distributed MIMO testbed.

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“…Though learning the CSI using reciprocity has been empirically shown feasible in many practical systems, e.g., [1,2], it however has two limitations. First, it requires hardware calibration [1], which incurs additional overhead and could be performed imperfectly, affecting accuracy of channel estimation.…”

Section: Introductionmentioning

confidence: 99%

An empirical study of analog channel feedback

Shen

Lin

Chen

2013

Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM

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Exchanging the channel state information (CSI) in a multiuser WLAN is considered an extremely expensive overhead. A possible solution to reduce the overhead is to notify the analog value of the CSI, which is also known as analog channel feedback. It however only allows nodes to overhear an imperfect channel information. While some previous studies have theoretically analyzed the performance of analog channel feedback, this work aims at addressing issues of realizing it in practice and empirically demonstrating its effectiveness. Our prototype implementation using USRP-N200 shows that analog channel feedback produces a small error comparable to that of estimating CSI using reciprocity, but however can be applied to more general scenarios.

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Random access heterogeneous MIMO networks

Cited by 51 publications

References 23 publications

Maximum MIMO Flow in wireless networks under the SINR model

Maximum MIMO Flow in wireless networks under the SINR model

Achieving high data rates in a distributed MIMO system

An empirical study of analog channel feedback

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