• ETRI Journal
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• v.30 no.3
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• pp.355-364
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• 2008

Multiple-input multiple-output (MIMO) systems can provide significant increments in capacity; however, the capacity of MIMO systems degrades severely when spatial correlation among multipath channels is present. This paper demonstrates that the influence of shadowing on the channel capacity is more substantial than that of multipath fading; therefore, the shadowing effect is actually the dominant impairment. To overcome the composite fading effects, we propose combining macroscopic selection diversity (MSD) schemes with MIMO technology. To analyze the system performance, the capacity outage expression of MIMO-based MSD (MSD-MIMO) systems using a characteristic function is applied. The analytic results show that there are significant improvements when MSD schemes are applied, even for the two-base-station diversity case. It is also observed that the effect of spatial correlation due to multipath fading is almost negligible when multiple base stations cooperatively participate in the mobile communication topology.

• 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.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.755-764
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• 2017

In this paper, we design transmitter and receiver structures for a $2{\times}2$ multiple-input multiple-output (MIMO) in ATSC 3.0 systems and analyze the performance of the $2{\times}2$ MIMO system. In the ATSC 3.0 MIMO systems, spatial diversity and multiplexing gains can be obtained using the spatial demultiplexer and precoder. In this paper, we present the structures of the transmitter and receiver for ATSC 3.0 MIMO systems. Also, we present performance results of the $2{\times}2$ MIMO system through computer simulations.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.338-351
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• 2013

Multiple-input multiple-output (MIMO) communication may provide high spectral efficiency through the deployment of a very large number of antenna elements at the base stations. The gains from massive MIMO communication come from the use of multi-user MIMO on the uplink and downlink, but with a large excess of antennas at the base station compared to the number of served users. Initial work on massive MIMO did not fully address several practical issues associated with its deployment. This paper considers the impact of channel aging on the performance of massive MIMO systems. The effects of channel variation are characterized as a function of different system parameters assuming a simple model for the channel time variations at the transmitter. Channel prediction is proposed to overcome channel aging effects. The analytical results on aging show how capacity is lost due to time variation in the channel. Numerical results in a multicell network show that massive MIMO works even with some channel variation and that channel prediction could partially overcome channel aging effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2797-2820
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• 2015

In order to accommodate huge number of antennas in a limited antenna size, a large scale antenna array is expected to have a three dimensional (3D) array structure. By using the Active Antenna Systems (AAS), the weights of the antenna elements arranged vertically could be configured adaptively. Then, a degree of freedom (DOF) in the vertical plane is provided for system design. So the three-dimension MIMO (3D MIMO) could be realized to solve the actual implementation problem of the massive MIMO. However, in 3D massive MIMO systems, the pilot contamination problem studied in 2D massive MIMO systems and the inter-cell interference as well as inter-vertical sector interference in 3D MIMO systems with vertical sectorization exist simultaneously, when the number of antenna is not large enough. This paper investigates the interference management towards the above challenges in 3D massive MIMO systems. Here, vertical sectorization based on vertical beamforming is included in the concerned systems. Firstly, a cooperative joint vertical beams adjustment and pilot assignment scheme is developed to improve the channel estimation precision of the uplink with pilots being reused across the vertical sectors. Secondly, a downlink interference coordination scheme by jointly controlling weight vectors and power of vertical beams is proposed, where the estimated channel state information is used in the optimization modelling, and the performance loss induced by pilot contamination could be compensated in some degree. Simulation results show that the proposed joint optimization algorithm with controllable vertical beams' weight vectors outperforms the method combining downtilts adjustment and power allocation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.4
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• pp.461-469
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• 2008

This paper proposes a hybrid symbol offset estimation algorithm for MIMO(Multiple Input Multiple Output) OFDM system. As MIMO OFDM systems are multiple transmitter and receiver antenna systems, apart from SISO(Single Input Single Output) system, it is possible to use several combining techniques which are used in multiple receive antenna system. In this paper, we propose hybrid symbol offset estimation algorithms using combining techniques in multiple receive antenna systems, simulate and show the performances in MIMO system environments. The proposed equal gain combining correlation algorithm has better performance 1.8 times in searching the ideal symbol offset rather than the conventional early symbol offset algorithm in severe ISI channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.413-423
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• 2014

With the increasing demands on high data rate, there has been growing interests in multi-input multi-output (MIMO) technology based on spatial multiplexing (SM) since it can transmit independent information in each spatial stream. Recent standards such as 3GPP LTE-advanced and IEEE 802.11ac support up to eight spatial streams, and massive MIMO and mm-wave systems that are expected to be included in beyond 4G systems are considering employment of tens to hundreds of antennas. Since the complexity of the optimum maximum likelihood based detection method increases exponentially with the number of antennas, low-complexity SM MIMO detection becomes more critical as the number of antenna increases. In this paper, we first review the results on the detection schemes for SM MIMO systems. In addition, massive MIMO reception schemes based on simple linear filtering which does not require exponential increment of complexity will be explained, followed by brief description on receiver design for future high dimensional SM MIMO systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1025-1031
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• 2007

This paper proposes an area-efficient pipeline FFT processor for MIMO-OFDM systems with four transmitting and four receiving antennas. Since the MIMO-OFDM system transmits multiple data streams, the complexity for the MIMO-OFDM system with a single-channel FFT processor increases linearly with the increase of the number of transmit channels. The proposed FFT processor is based on multi-channel structure, and therefore it can efficiently support multiple data streams. With the mixed radix algorithm, the number of non-trivial multiplications of the proposed FFT processor is decreased. The proposed FFT processor is synthesized with CMOS $0.18{\mu}m$ process and reduces the logic gates by 25% over a 4-channel Radix-4 multi-path delay commutator (R4MDC) FFT processor. Since the MIMO-OFDM FFT processor is one of the largest modules in the systems, the proposed FFT processor will be a vast contribution improvement to the low complexity design of MIMO-OFDM systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.232-240
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• 2011

While the water-filling algorithm is an efficient power allocation method that maximizes the ergodic capacity of adaptive MIMO systems, its excessive residual power causes spectrum loss in real systems employing discrete modulation indices. In this paper we propose new power allocation algorithms that improve the spectral efficiency of MIMO systems by efficiently reallocating the residual power of the water-filling algorithm. We apply the proposed algorithms to the adaptive turbo-coded MIMO system to verify their performance through computer simulation in various environments. Simulation results show that the spectral efficiency of the proposed algorithms is better than that of the water-filling algorithm by about 8.9% at SNR of 20dB in Rayleigh fading environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.