• Journal of Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1238-1243
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• 2007

The computational complexity for the zero-forcing (ZF)-based multiuser (MU) multiple-input multiple-output(MIMO) preprocessing matrices can be immoderately large as the number of transmit antennas or users increases. In this paper, we show that the span of singular vector space of a matrix can be obtained from the singular vectors of the parted rows of that matrix with computational saving and propose a computationally efficient recursive-algorithm for achieving the ZF-based preprocessing matrices. Analysis about the complexities shows that a new recursive-algorithm can lighten the computational load.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.112-117
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• 2007

In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.254-264
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• 2007

A promising approach to improve the performance of mobile location system is the use of antenna arrays in both transmitter and receiver sides. Using advanced array signal processing techniques, such multiple-input multiple-output (MIMO) communication systems can offer more mobile location information by exploiting the spatial properties of the multipath channel. In this paper, we propose a novel approach to determine the position of mobile terminal based on estimated multipath signal parameters using only one base station in MIMO communication systems. This approach intends to minimize the error occurring from the estimation of multiple paths and gives an optimal estimation of the position of mobile terminal by simultaneously calculating a set of nonlinear location equations. This solution breaks the bottleneck of conventional mobile location systems which have to require multilateration of at least three base stations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1889-1910
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• 2017

This paper investigates a protocol so-called Adaptive Harvest Then Transmit (AHTT) for wireless powered communication networks (WPCNs) in multiple-input single-output (MISO) downlink systems, which assists in transmitting signals from a multi-antenna transmitter to a single-antenna receiver. Particularly, the power constrained relay is supplied with power by utilizing radio frequency (RF) signals from the source. In order to take advantage of multiple antennas, two different linear processing schemes, including Maximum Ratio Combining (MRC) and Selection Combination (SC) are studied. The system outage capacity and ergodic capacity are evaluated for performance analysis. Furthermore, the optimal power allocation is also considered. Our numerical and simulation results prove that the implementation of multiple antennas helps boost the energy harvesting capability. Therefore, this paper puts forward a new way to the energy efficiency (EE) enhancement, which contributes to better system performance.

• Journal of Communications and Networks
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• v.8 no.2
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• pp.194-204
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• 2006

This contribution focuses on the maximum likelihood (ML) noncoherent synchronization of multi-antenna transceivers working in faded environments and employing ultra-wideband impulse radio (UWB-IR) transmit technology. In particular, the Cramer-Rao bound (CRB) is derived for the general case of multiple input multiple output (MIMO) UWB-IR systems and used to compare the ultimate performance of three basic transmit schemes, thereinafter referred to as single input multiple output (SIMO), MIMO equal signaling (MIMO-ES), and MIMO orthogonal signaling (MIMO-OS) ones. Thus, the noncoherent ML synchronizer is developed for the better performing transmit scheme (i.e., the SIMO one) and its performance is evaluated under both signal acquisition and tracking operating conditions. The performance gain in the synchronization of UWB- IR signals arising by the utilization of the multi-antenna technology is also evaluated.

• ETRI Journal
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• v.41 no.5
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• pp.637-647
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• 2019

Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple-input multiple-output (MU-MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal-to-interference-plus-noise ratio (SINR) loss to characterize it in multiuser multiple-input single-output (MU-MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU-MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU-MISO systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1485-1491
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• 2015

This paper introduces a new pilot assignment algorithm for uplink Massive multiple-input multiple-output (MIMO) systems. Since the conventional pilot assignment algorithm has the performance degradation compared to the optimal algorithm which performs the exhaustive search, we propose a new pilot assignment algorithm using Pre-determined Interference and Pre-determined Desired-term techniques. The proposed algorithm has the low complexity and guarantees negligible performance loss compared to the optimal algorithm. Simulation result verifies that the proposed algorithm achieves a large performance gain over the conventional algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.830-839
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• 2009

In this paper, we address a near maximum likelihood (ML) scheme for the decoding of multiple input multiple output systems. Based on the metric-first search method and by employing Schnorr-Euchner enumeration and branch length thresholds, the proposed scheme provides reduced computational complexity. The proposed scheme is shown by simulation to have lower computational complexity than other near ML decoders while maintaining the bit error rate close to the ML performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.587-593
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• 2010

In this paper we design an irregular low-density parity-check (LDPC) code for multiple-input multiple-output (MIMO) system, using a simple extrinsic information transfer (EXIT) chart method. The MIMO systems considered are optimal maximum a posteriori probability (MAP) detector. The MIMO detector and the LDPC decoder exchange soft information and form a turbo iterative receiver. The EXIT charts are used to obtain the edge degree distribution of the irregular LDPC code which is optimized for the MIMO detector. It is shown that the performance of the designed LDPC code is better than that of conventional LDPC code which was optimized for either the Additive White Gaussian Noise (AWGN) channel or the MIMO channel.