• ETRI Journal
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• v.36 no.4
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• pp.682-685
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• 2014

In this letter, we propose an efficient near-optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi-user multiple-input multiple-output (MU-MIMO) systems. In practical MU-MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near-optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.

• ETRI Journal
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• v.36 no.4
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• pp.564-571
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• 2014

Sphere decoding (SD) for multiple-input and multiple-output systems is a well-recognized approach for achieving near-maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM-MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal-to-noise ratio regime. To demonstrate the potential of our method, we compare the results with another well-known method - namely, probabilistic tree pruning SD.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.141-149
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• 2007

Multiple-input multiple-output (MIMO) transmit pre-coding/beamforming can significantly improve system spectral efficiency. However, several obstacles prevent precoding from wide deployment in early wireless networks: The significant feedback overhead, performance degradation due to feedback delay, and the large storage requirement at the mobile devices. In this paper, we propose a precoding method that addresses these issues. In this approach, only 3 or 6 bits feedback is needed to select a precoding matrix from a codebook. There are fifteen codebooks, each corresponding to a unique combination of antenna configuration (up to 4 antennas) and codebook size. Small codebooks are prestored and large codebooks are efficiently computed from the prestored codebook, modified Hochwald method and Householder reflection. Finally, the feedback delay is compensated by channel prediction. The scheme is validated by simulations and we have observed significant gains comparing to space-time coding and antenna selection. This solution was adopted as a part of the IEEE 802.16e specification in 2005.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.136-140
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• 2007

In this paper, an adaptive minimum transmit power modulation scheme under constant data rate and fixed bit error rate (BER) for the multiple-input multiple-output (MIMO) system is proposed. It adjusts the modulation order and allocates the transmit power to each spatial sub-channel when meeting the user's requirements at the cost of minimum transmission power. Compared to the other algorithm, it can obtain good performance with lower computational complexity and can be applied to the wireless communication system. Computer simulation results present the efficiency of the proposed scheme. And its performance under different channel condition has been compared with the other algorithm.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.649-657
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• 2016

In this paper, we investigate energy efficiency (EE) of the traditional co-located and the distributed massive multiple-input multiple-output (MIMO) systems. First, we derive an approximate EE expression for both the idealistic and the realistic power consumption models. Then an optimal energy-efficient remote access unit (RAU) selection algorithm based on the distance between the mobile stations (MSs) and the RAUs are developed to maximize the EE for the downlink distributed massive MIMO systems under the realistic power consumption model. Numerical results show that the EE of the distributed massive MIMO systems is larger than the co-located massive MIMO systems under both the idealistic and realistic power consumption models, and the optimal EE can be obtained by the developed energy-efficient RAU selection algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.330-335
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• 2008

This paper proposes a packet detection algorithm for IEEE802.11n system. IEEE802.11n is a multiple input multiple output (MIMO) system and we have to consider several combining techniques which are used in multiple receive antenna system. In this paper, we propose a hybrid packet detection algorithm which combines double sliding window algorithm or delay and correlation algorithm, that is used in single input single output (SISO) system, and multiple receive antenna combining algorithms, and simulated their performances in Iin system environments and shows the results.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.385-390
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• 2011

In this paper, various ultra-wideband (UWB) spatial multiplxing (SM) multiple input multiple output (MIMO) receivers based on a prerake diversity combining scheme are discussed and their performance is analyzed. Several UWB MIMO detection approaches such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC), sorted QR decomposition (SQRD), and maximum likelihood (ML) are considered in order to cope with inter-channel interference. The UWB SM systems based on transmitter-side multipath preprocessing and receiver-side MIMO detection can either boost the transmission data rate or offer significant diversity gain and improved BER performance. The error performance and complexity of linear and nonlinear detection algorithms are comparatively studied on a lognormal multipath fading channel.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.143-146
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• 2009

In this paper, we investigated the list sphere decoders (LSD) for multiple-input multiple-output (MIMO) systems. We showed that the ordering procedures play an important role in LSD in order to achieve the low complexity without degrading the bit-error-rate (BER) performance. Then, we proposed a novel ordering algorithm for the LSD which uses a look-up table and simply comparative operations. Comparative results in terms of BER performance and computational complexity are provided through computer simulations.

• ETRI Journal
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• v.41 no.2
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• pp.145-159
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• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.