An Opportunistic Beamforming Technique Using a Quantized Codebook

Kang, Ji-Won; Choi, In-Kyeong; Kwon, Dongseung; Lee, Chungyong

doi:10.1109/vetecs.2007.343

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Combining (58) and (59) with (23) and (24) first, and then these results with (35) and (41), the desired closed form approximation for the first two raw moments of g k ⋆ are obtained when OCP-Proj scheme is used with M ≥ 4.…”

Section: B Opportunistic Cophasing Schemementioning

confidence: 98%

“…After that, based on the a priori knowledge of the RBF vector that will be applied in the following scheduling interval, the M2M device will be able to estimate the effective channel gain that will be perceived [11]. Note that a similar approach has been employed in [23] to provide further MUD gain in OBF systems, by means of increasing the number of beam candidates that can be chosen when the number of devices in the system is small. At first glance, this design criteria could be interpreted as contradictory with respect to the one introduced in [4].…”

Section: Opportunistic Cophasing With Quantized Channel State Infmentioning

confidence: 99%

“…Therefore, in case of an M2M communication scenario with a moderate numbers of devices, only a small fraction of the available MUD gain is expected to be exploited, particularly when deploying large antenna arrays at the BS (i.e., when M > 4). To overcome this limitation, multi-beam techniques can be used to increment the chance of having a device in beamforming configuration, enhancing system performance in such circumstances [23].…”

Section: Effect Of Parameter N On Snr Gain Of Ocp-proj Schemementioning

confidence: 99%

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Performance of Quantized Random Beamforming in Delay-Tolerant Machine-Type Communication

Dowhuszko

Corral-Briones

Hämäläinen

et al. 2016

IEEE Trans. Wireless Commun.

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Machine-to-Machine (M2M) communication represents a new paradigm for mobile cellular networks, where a massive number of low-cost devices requests the transfer of small amounts of data without human intervention. One option to tackle this problem is obtained by combining Random Beamforming (RBF) with opportunistic scheduling. RBF can be used to induce larger channel fluctuations and opportunistic scheduling can be used to select M2M devices when their overall channel quality is good. Traditional RBF does not fulfill M2M requirements because overall channel quality needs to be tracked continuously. In order tackle this limitation, a novel codebookbased RBF architecture that identifies in advance the time instants in which overall channel quality should be reported, within a coherence time window, is proposed. This opportunistic feedback mechanism reduces signaling overhead and enables energy saving at M2M devices. A simplified methodology is presented to evaluate the system mean data rate, using for this purpose closed form formulas derived from SNR distribution approximations. Results reveal that the performance loss that is experienced for introducing the proposed modifications to traditional RBF scheme is negligible. The concepts analyzed in this paper provide useful insights, and show that codebook-based RBF with simplified opportunistic scheduling algorithms is an excellent combination to provide wide-area M2M services with low-cost devices and limited signaling overhead.

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Section: B Opportunistic Cophasing Schemementioning

confidence: 98%

Section: Opportunistic Cophasing With Quantized Channel State Infmentioning

confidence: 99%

Section: Effect Of Parameter N On Snr Gain Of Ocp-proj Schemementioning

confidence: 99%

See 1 more Smart Citation

Performance of Quantized Random Beamforming in Delay-Tolerant Machine-Type Communication

Dowhuszko

Corral-Briones

Hämäläinen

et al. 2016

IEEE Trans. Wireless Commun.

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“…It is claimed that the faster the fading is, the less weight vectors are desired; and the more users there are, the less weight vectors are desired. To overcome the problem of limited multiuser diversity in a small population, [12] devises a codebook-based OBF (COBF) technique, where the employed unitary matrix changes with time slot to induce larger and faster channel fluctuations in the static channel and to provide further selection diversity to the conventional OBF technique. Compared with [10], the COBF technique reduces the required number of mini-time slots, and, since it is the size of codebook, not the number of mini-time slots, that determines the amount of supplementary selection diversity, the system throughput can be increased without limitation from the number of mini-time slots.…”

Section: Introductionmentioning

confidence: 99%

Generation of Multiple Weights in the Opportunistic Beamforming Systems

Lu¹,

Zhang²,

Yu³

et al. 2009

WSN

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A new scheme to generate multiple weights used in opportunistic beamforming (OBF) system is proposed to deal with the performance degradation due to the fewer active users in the OBF system. In the proposed scheme, only two mini-slots are employed to create effective channels, while more channel candidates can be obtained via linearly combining the two effective channels obtained during the two mini-slots, thus increas-ing the multiuser diversity and the system throughputs. The simulation results verify the effectiveness of the proposed scheme

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