• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.49-52
• /
• 2008

In this letter, we derive a tight closed form formula for an ergodic rapacity of a multiple-input multiple-output (MIMO) for the application of wireless communications. The derived expression is a simple close-form formula to determine the ergodic capacity of MIMO systems. Assuming the channels are independent and identically distributed (i.i.d.) Rayleigh flat-fading between antenna pairs, the ergodic capacity can be expressed in a closed form as the finite sum of exponential integrals.

• Journal of electromagnetic engineering and science
• /
• v.11 no.2
• /
• pp.71-75
• /
• 2011

The sum-rate maximization rule can find an optimal user set that maximizes the sum capacity in multiple input multiple output (MIMO) broadcast channels (BCs), but the search space for finding the optimal user set becomes prohibitively large as the number of users increases. The proposed algorithm selects a user set of the largest effective channel norms based on statistical channel state information (CSI) for reducing the computational complexity, and uses Tomlinson-Harashima precoding (THP) for minimizing the interference between selected users in time-varying MIMO BCs.

• International journal of advanced smart convergence
• /
• v.7 no.3
• /
• pp.37-43
• /
• 2018

Lattice-reduction (LR) techniques have been developed for signal detection in spatial multiplexing multiple input multiple output (MIMO) systems to obtain the largest diversity gain. Thus, an LR-assisted zero-forcing (ZF) receiver can achieve the maximum diversity gain in spatial multiplexing MIMO systems. In this paper, a simplified analysis of the achievable diversity gain is presented by fitting the channel coefficients lattice-reduced by a complex Lenstra-Lenstra-$Lov{\acute{a}}z$ (LLL) algorithm into approximated Gaussian random variables. It will be shown that the maximum diversity gain corresponding to two times the number of receive antennas can be achieved by the LR-based ZF detector. In addition, the approximated bit error rate (BER) expression is also derived. Finally, the analytical BER performance is comparatively studied with the simulated results.

• Journal of electromagnetic engineering and science
• /
• v.14 no.4
• /
• pp.349-352
• /
• 2014

This paper considers the multiple-input multiple-output (MIMO) system with linear minimum mean square error (MMSE) detection under ideal fast fading. For $N_t$ transmit and $N_r({\geq}N_t)$ receive antennas, we derive the achievable ergodic capacity of MMSE detection exactly. When MMSE detection is considered in a receiver, we introduce a different approach that gives the approximation of a MIMO channel capacity at high signal-to-noise ratio (SNR). The difference between the channel capacity and the achievable capacity of MMSE detection converges to some constant that depends only on the number of antennas. We validate the analytical results by comparing them with Monte Carlo simulated results.

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

• Journal of Advanced Information Technology and Convergence
• /
• v.10 no.1
• /
• pp.1-14
• /
• 2020

Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.481-482
• /
• 2007

This paper demonstrates OFDM with adaptive modulation applied to Multiple-Input Multiple-Output (MIMO) systems. We apply an optimization algorithm to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The analysis and simulation is considered in two stages. The first stage involves the application of a variable-rate variable-power MQAM technique for a Single-Input Single-Output(SISO) OFDM system. This is compared with the performance of fixed OFDM transmission where a constant rate is applied to each subcarrier. The second stage applies adaptive modulation to a general MIMO system by making use of the Singular Value Decomposition to separate the MIMO channel into parallel subchannels. For a two-input antenna, two-output antenna system, the performance is compared with the performance of a system using selection diversity at the transmitter and maximal ratio combining at the receiver.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.18-19
• /
• 2008

In this paper, we define the normalized mean square covariance (MIMO) of multiple input multiple output (MIMO) channels and study the relationship between ergodic MIMO channel capacity and the channel NMSV value.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.9A
• /
• pp.1022-1030
• /
• 2004

The next generation cellular radio systems require high data rate transmission and large system capacity In order to meet these requirements, multiple antennas can be used at the base and mobile stations, forming MIMO(multiple-input, multiple-output) channels This paper considers a downlink MIMO system assuming a large number of base station antennas, a small number of mobile station antennas, and rich-scattering, quasi-stationary, and flat-fading channel environments When the channel state information is given at the base station in a single user system, a MIMO technique with SVD(singular value decomposition) and water-filling can achieve the maximal downlink channel capacity. In multi-user environments, however, SDMA(space division multiple acces) technique can be used to further increase the total channel capacity supported by the base station This paper proposes a MIMO SDMA technique which can transmit parallel data streams to each of multiple users. The proposed method. can achieve higher total channel capacity than SVD-based MIMO techniques or conventional SDMA using smart antennas.

• 한국정보통신설비학회:학술대회논문집
• /
• 2008.08a
• /
• pp.525-530
• /
• 2008

There are a few core technologies to enable high-performance $4^{th}$ generation (4G) broadband wireless communication system. A multiple input multiple output (MIMO) provides high-rate transmission through expended channels by multiple array antennas in both sender and receiver side. Also orthogonal frequency division multiplexing (OFDM) is well-known as the most appropriate technique for high data rate transmission such as Mobile WiMAX and WLAN. Efficient decrease of inter-carrier interference (ISI) and inter-carrier interference (ICI) are the reasons for why OFDM is suitable for high-performance transmission, 4G mobile communication. In this paper, we mainly focus on two of objects, combination between MIMO and OFDM, and OFDM channel simulator using Ray-tracing algorithm. The results of this paper can be used implementation of a Wireless Software Platform for 4G Mobile Communication Systems.