On the Feasibility of Distributed Beamforming in Wireless Networks

Mudumbai, Raghuraman; Barriac, G.; Madhow, Upamanyu

doi:10.1109/twc.2007.360377

Cited by 445 publications

(256 citation statements)

References 11 publications

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“…An algorithm that yields impressive results through the use of a single bit of feedback from the receiver to the transmitters has been recently proposed [3]. Both analysis [4], [5] and experimental prototyping [6] have confirmed its advantages.…”

Section: Introductionmentioning

confidence: 97%

Distributed beamforming with binary signaling

Johnson

Mitzenmacher

Ramchandran

2008

2008 IEEE International Symposium on Information Theory

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Abstract-We consider a distributed beamforming problem in which nodes are restricted to sending binary phases to a receiver that has access to a one-bit feedback channel. Our simplified model allows us to prove lower bounds, as well as explore algorithmic techniques and analyses. We demonstrate both upper and lower bounds on the convergence time that are linear in the number of nodes in the system. Our upper bound is given by analyzing a simple randomized algorithm. We also discuss methods for accurately approximating the convergence time numerically that apply to our algorithm, as well as more general algorithms. Finally, we investigate modifications of the basic algorithm which improve the constant factor in the running time.

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Section: Introductionmentioning

confidence: 97%

Distributed beamforming with binary signaling

Johnson

Mitzenmacher

Ramchandran

2008

2008 IEEE International Symposium on Information Theory

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“…The transmission of data can be greatly reduced by increasing a little energy consumption in processor, thus further reducing energy consumption. Beamforming algorithm is a typical data fusion algorithm [10].At the same time, when the calculated load of processing module is low, the dynamic voltage regulation (DVS) technology can be used [11].…”

Section: Analysis and Countermeasures Of System Energy Consumptionmentioning

confidence: 99%

Energy Saving Supply System Design Based on Wireless Sensor Network

Sun¹

2017

Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

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Abstract. Wireless sensor network (WSN) is a new generation of sensor networks, which has an extensive application prospect, but the energy limitation of sensor nodes is a key issue of WSN. This paper designs a kind of energy saving supply system which is applied to WSN. The system makes full use of the electric energy to charge up and restore the electric energy into battery. When a network node (or key node) in the system needs to be charged, the system makes use of the routing algorithm to find an optimal power supply path to charge the node in the way of wireless charging.Firstly, the system divided sensor nodes into two types: common type and energy storage type. Secondly, according to the distribution of wireless sensor nodes in the system, the sensor nodes are divided into different areas for management and the energy management area centering on energy storage sensor nodes is established. Energy transfer path between sensor nodes among the whole network will be stored in an energy storage sensor node in the form of an optimal path tree (SPF tree) or its branch so as to achieve energy coverage for all sensor nodes. Finally, the problem of energy consumption of the system is analyzed and some solutions are put forward to extend the service life of WSN. For this system, there are still a lot of work to be done in the further optimization of energy management strategy and the further reduction of energy consumption. Further research on these problems is expected to be done in the future.

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“…A cross-layer approach to DB for wireless ad-hoc networks is discussed in [19] with more complicated models and two time phases of communication steps. The improved beampattern and connectivity properties are shown in [20], and a reasonable beamforming performance with node synchronization error is discussed in [21]. DB requires accurate synchronization; in other words, the sources must transmit at the same time, synchronize their carrier frequencies and control their carrier phases so that their signals can be combined constructively at the destination.…”

Section: Distributed Beamforming: a New Concept Beamforming Techniquementioning

confidence: 99%

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Lian

Nikookar

Ligthart

2011

Wireless Pers Commun

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In this paper, we introduce Adaptive Beamforming (AB) and Distributed Beamforming (DB) as two efficient techniques for Intelligent WiMAX (I-WiMAX). I-WiMAX is a new maritime communication system, consisting of Smart Radio (SR) principles and mobile WiMAX based on the IEEE 802.16e standard. Adopting AB, the same spectrum can accommodate more users by directing the main beam towards desired users while antenna pattern nulls towards others. To reduce the channel interferences caused by spectrum reusing, the Null Broadening (NB) method is required for downlink beamforming of I-WiMAX. A new NB method is presented in this paper with iterative weights computing for different OFDM subcarriers. Considering the spatial channel model seen at Subscriber Stations (SS) based on the von Mises distribution, the coverage range of one Base Station (BS) is dramatically enlarged by employing the NB technique. Meanwhile, assuming those SS which are within the coverage range as nodes of a relay network, the DB technique is introduced to forward signals to distant SS by forming the main beams towards them instead of deploying more BS to increase the communication range. It is proven in this paper that DB can successfully do the job. To reuse the spectrum, two DB methods are presented by directing different beams towards different required directions at the same time. With the AB and DB techniques, reliable I-WiMAX links can be established for long distances, with more optimum spectrum use and less infrastructure.

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On the Feasibility of Distributed Beamforming in Wireless Networks

Cited by 445 publications

References 11 publications

Distributed beamforming with binary signaling

Distributed beamforming with binary signaling

Energy Saving Supply System Design Based on Wireless Sensor Network

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

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