Kyungsik Min

Spatial resource utilization to maximize uplink spectral efficiency in full-duplex massive MIMO

In this paper, we consider a full-duplex massive MIMO system which includes a full-duplex BS with a large number of antennas and half-duplex uplink (UL) and downlink (DL) users with a single antenna. Due to the self-interference at the BS, the UL spectral efficiency is significantly decreased. In order to improve the UL spectral efficiency, we focus on the utilization schemes of the spatial resources which can be used to enhance the UL performance. If the BS uses the spatial resources as receive antennas, the BS can obtain an additional receive diversity gain for the UL desired signal. On the other hand, if the BS uses the spatial resources as transmit antennas, the BS can suppress a part of the self-interference by using the extended transmit beamformer including a part of the self-interference channel. Our analysis and numerical results show that there are some tradeoffs between achieving receive diversity gain for the UL desired signal and suppressing the self-interference. According to the system parameters, the utilization schemes of the spatial resources would be determined for maximizing the UL spectral efficiency.

Asymptotic Distribution of System Capacity in Multiuser MIMO Systems with Large Number of Antennas

In this paper, an asymptotic distribution for the sum rate capacity is derived in zero-forcing beamforming (ZF-BF) based multiuser MIMO systems with a large number of base station (BS)antennas. By utilizing the characteristics of a large number of antennas and the central limit theorem, we prove that the asymptotic distribution for the sum rate capacity follows Gaussian distribution. Also we derive the mean and variance values for the asymptotic Gaussian distribution. Based on the asymptotic Gaussian distribution, we also obtain the outage probability for the sum rate capacity as a closed form. Simulation results show that the asymptotic Gaussian distribution is well follows the actual sum rate capacity, and the both asymptotic mean and variance value are also very accurate.

Antenna ratio for sum-rate maximization in MU-MIMO with full-duplex large array BS

This paper analyzes the ratio of the transmit antennas and receive antennas in multi-user multiple-input multipleoutput with a full-duplex and large array base station (BS) and half-duplex users (MU-MIMO FLB-HU) systems. We consider the BS exploits zero-forcing beamformer and zero-forcing receiver. We derive the deterministic approximation of the downlink and uplink sum-rates considering inter-user interference and self-interference, respectively. Based on the analyzed results, we formulate an optimization problem in terms of the number of transmit and receive antennas to maximize the sum of downlink and uplink sum-rates subject to the number of total antennas at the BS. From the optimization problem, the optimal antenna ratio between the number of transmit and receive antennas can be obtained. We analyze that the optimal antenna ratio converges to the ratio between the number of downlink users (Kd) and uplink users (Ku) as the number of total antennas goes to infinity. Simulation results show that the optimal antenna ratio enhances the sum-rate performance compared to the same number of transmit antennas and receive antennas in the MU-MIMO FLBHU system. In particular, in the MU-MIMO FLB-HU system with Kd = 10 and Ku = 5, the optimal antenna ratio can achieve about 5~10bps/Hz performance gain compared to the same number of transmit antennas and receive antennas.

Antenna Ratio for Sum-Rate Maximization in Full-Duplex Large-Array Base Station with Half-Duplex Multiantenna Users

This paper analyzes the ratio of transmit antennas to receive antennas at the base station (BS) in full-duplex multiuser multiple-input-multiple-output (MU-MIMO) systems with large-array BS and half-duplex multiantenna users. We consider a full-duplex BS with a block diagonalization (BD) precoder for downlink transmission and a BD receive filter for uplink reception. We derive the approximated downlink sum-rate considering the inter-user interference, and the uplink sum-rate considering the self-interference (SI), for large numbers of BS antennas. Based on the analysis, we formulate an optimization problem in terms of the ratio of transmit antennas to receive antennas to maximize the sum-rate. The analysis shows that the antenna ratio for maximizing the sum rate converges to the ratio of downlink streams to uplink streams as the number of total BS antennas goes to infinity. Simulation results confirm the analysis and show that the BS using the derived antenna ratio in the full-duplex MU-MIMO system can achieve about a 10~20 b/s/Hz performance gain compared with the BS using an equal number of transmit and receive antennas.

Study on effect of training for downlink massive MIMO systems with outdated channel

In this paper, we analyze the effect of uplink and downlink training on the downlink achievable rate for massive MIMO systems with outdated channel. Even though both uplink and downlink training have the same training overhead, the achievable rate is more dominated by the uplink training than downlink training. As the number of antennas goes to infinity, the performance gain of the downlink training is negligible. This fact implies that non-coherent detection is more desirable for massive MIMO systems in terms of throughput. The rate loss caused by outdated channel is also dominated by the uplink training. Our analysis gives a good insight to implement practical massive MIMO systems.

Performance evaluation of various small-cell deployment scenarios in small-cell networks

In this paper, we study the effective small-cell deployment scenarios to improve the system performance. We consider three deployment strategies - the random deployment, the deployment for the worst-performance user, and the cell-edge deployment [1]. From the system level simulation results, we suggest the effective small-cell deployment strategy in terms of the signal-to-interference plus noise ratio performance.

Pilot Power Ratio for Uplink Sum-Rate Maximization in Zero-Forcing Based MU-MIMO Systems with Large Number of Antennas

This paper analyzes the pilot power ratio (PPR) in multiuser multiple-input multiple-output (MU-MIMO) systems with a large number of receive antennas (M) at the base station (BS). We consider zero-forcing based MU-MIMO orthogonal frequency division multiplexing (OFDM) systems. Based on the deterministic uplink sum-rate approximation for imperfect channel state information, we can formulate the optimization problems in terms of the PPR to maximize the ergodic uplink sum-rate subject to the per-slot or per-symbol power constraint. Under the per-slot power constraint, the optimal PPR can be obtained in a closed form while under the per-symbol power constraint, we propose an iterative algorithm which generates a suboptimal PPR. Simulation results show that the proposed PPRs perform close to the optimal performance in terms of the sum-rate. Also, it is shown that the proposed PPRs outperform the equal power allocation. In particular, in the ZF-R based MU-MIMO OFDM system with 8 users and M=32 under the per-slot power constraint, the proposed PPR can achieve about 8bps/Hz performance gain compared to the equal power allocation.

Multiuser CQI prediction based on quantization error feedback for massive MIMO systems

In this paper, multiuser channel quality indicator (MU-CQI) prediction based on channel quantization error feedback is proposed for massive multiple-input multiple-output (MIMO) systems. Basically, CQI reporting in the practical systems is performed based on the single user (SU) MIMO transmission mode to keep low feedback overhead and computational complexity. To operate in MU-MIMO transmission mode, the base station needs to predict the MU-CQI from the reported SU-CQI. The conventional CQI update method is based on the worst-case approach to minimize the outage probability. However, this is not efficient way for the massive MIMO systems, since there is a lot of capacity loss when the number of served users is large. To improve the accuracy of prediction, we propose MU-CQI prediction method based on channel quantization error feedback. Although the proposed scheme requires few feedback overhead like only 1bit, it shows remarkable performance gain compared to the conventional prediction scheme in terms of system goodput.

Statistical Beamforming Based on Effective Channel Gain for Spatially Correlated Massive MIMO Systems

A statistical beamforming (SBF) scheme based on the effective channel gain (ECG) is proposed for spatially correlated massive multiple-input multiple-output systems. The proposed SBF scheme consists of outer and inner precoders. The outer precoder is designed to eliminate multiuser interference based on the correlation matrix of downlink channel. Then, according to the ECG defined as the squared inner product of the dedicated channel and an arbitrary precoding vector, the inner precoder is selected among the eigenvectors of the dedicated channel’s correlation matrix with the maximum ECG. Simulation results show that the proposed SBF scheme outperforms conventional schemes.

System Level Simulation of mmWave Based Mobile Xhaul Networks

To support tens of Giga-bits/second (Gbps) data rate, 5G mobile communication systems consider the integration of backhaul and fronthaul links into Xhaul networks. This paper introduces the system-level simulation for mmWave based mobile Xhaul networks. Network scenarios, hybrid beamforming, with large antenna elements, and link-level models are discussed based on the results of the system-level simulation for the mobile Xhaul network. System-level simulation results show that the mobile Xhau network using a 40 GHz carrier frequency band can support a 20 Gbps data rate.