| 1. |
- Alodeh, M., et al.
(författare)
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A multicast approach for constructive interference precoding in MISO downlink channel
- 2014
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Ingår i: 2014 IEEE International Symposium on Information Theory. - : IEEE conference proceedings. ; , s. 2534-2538
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Konferensbidrag (refereegranskat)abstract
- This paper studies the concept of jointly utilizing the data information (DI) and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO) downlink channel. In this direction, the interference among the simultaneous data streams is transformed to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmissions (MRT) based algorithm that jointly exploits DI and CSI to gain the benefits from these useful signals. In this context, a novel framework to minimize the power consumption is proposed by formalizing the duality between the constructive interference downlink channel and the multicast channels. The numerical results have shown that the proposed schemes outperform other state of the art techniques.
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| 2. |
- Alodeh, M., et al.
(författare)
-
Joint channel estimation and pilot allocation in underlay cognitive MISO networks
- 2014
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Ingår i: 2014 International Wireless Communications and Mobile Computing Conference (IWCMC). - : IEEE conference proceedings. ; , s. 797-802
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Konferensbidrag (refereegranskat)abstract
- Cognitive radios have been proposed as agile technologies to boost the spectrum utilization. This paper tackles the problem of channel estimation and its impact on downlink transmissions in an underlay cognitive radio scenario. We consider primary and cognitive base stations, each equipped with multiple antennas and serving multiple users. Primary networks often suffer from the cognitive interference, which can be mitigated by deploying beamforming at the cognitive systems to spatially direct the transmissions away from the primary receivers. The accuracy of the estimated channel state information (CSI) plays an important role in designing accurate beamformers that can regulate the amount of interference. However, channel estimate is affected by interference. Therefore, we propose different channel estimation and pilot allocation techniques to deal with the channel estimation at the cognitive systems, and to reduce the impact of contamination at the primary and cognitive systems. In an effort to tackle the contamination problem in primary and cognitive systems, we exploit the information embedded in the covariance matrices to successfully separate the channel estimate from other users' channels in correlated cognitive single input multiple input (SIMO) channels. A minimum mean square error (MMSE) framework is proposed by utilizing the second order statistics to separate the overlapping spatial paths that create the interference. We validate our algorithms by simulation and compare them to the state of the art techniques.
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| 3. |
- Alodeh, M., et al.
(författare)
-
Spatial DCT-based least square estimation in multi-antenna multi-cell interference channels
- 2014
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Ingår i: 2014 IEEE International Conference on Communications (ICC). - : IEEE conference proceedings. ; , s. 4729-4734
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Konferensbidrag (refereegranskat)abstract
- Interference management techniques in multicell multiple input multiple output (MIMO) networks require accurate channel state information (CSI). A popular technique for acquiring this CSI in time division duplex (TDD) systems is uplink training by exploiting the reciprocity of the wireless medium. Recently, the pilot contamination problem has been identified as one of the limiting factors for such kind of CSI acquisition. In an effort to tackle the problem of contamination, we utilize the compression capability of discrete cosine transform (DCT) and covariance matrices to spatially separate the estimate for the scenario of correlated single input multiple input (SIMO) channels. A least square estimation framework is proposed by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across the interfering users. We validate our algorithms by simulation and compare them to the state of the art techniques.
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