Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the base station. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the base station. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the base station is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using predesigned patterns. The proposed method modifies the feedback packet by introducing the concept of a header to select a suitable group pattern and a payload to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.

Antenna Grouping Based Feedback Compression for FDD-Based Massive MIMO Systems

In this paper, the authors consider the adaptive-gain M -relay amplify-and-forward (AF) cooperative system with both conventional relaying (\cr), as well as a best-relay-selection (br) scheme, and investigate its performance over time-selective fading, due to nodes' mobility, in the presence of channel estimation errors. The authors first derive exact closed-form expressions for the destination's direct path and overall end-to-end instantaneous signal-to-noise ratios (SNRs). The authors also derive closed-form tight approximate expressions for the system average bit error rate, outage probability, and Shannon capacity, which are general functions of the cooperating nodes' relative speeds, in terms of the links' correlation parameters, the estimation errors' variances, and the receivers' tracking loops' channel estimation rates, in terms of the transmitted block length. The authors analysis reveals that due to the cooperating nodes' mobility, the system performance metrics are severely degraded and, in some particular network circumstances, experience asymptotic limits. In addition, when both of the source and the destination are static, the system performance does not experience asymptotic limits although the relays are in motion. On the other hand, despite that the relays are static, the mobility of either the source or the destination severely impacts the system performance by asymptotic limits, where the difference between their impacts depends on the symmetrical conditions of the network two-hop fading gain power. In addition, the authors found that the br provides higher asymptotic error limits than that of the /cr scheme. The authors also assured the special case when the network receivers are equipped with fast estimation loops and showed their effect of reducing the degradation impacts of the nodes' mobility. Simulation and numerical results are provided to verify the accuracy of the derived analytical expressions.

Performance Analysis of Multiple-Relay AF Cooperative Systems Over Rayleigh Time-Selective Fading Channels With Imperfect Channel Estimation

Fifth generation wireless standards require much lower latency than what current wireless systems can guarantee. The main challenge in fulfilling these requirements is the development of short packet transmission, in contrast to most of the current standards, which use a long data packet structure. Since the available training resources are limited by the packet size, reliable channel and interference covariance estimation with reduced training overhead are crucial to any system using short data packets. In this paper, we propose an efficient receiver that exploits useful information available in the data transmission period to enhance the reliability of the short packet transmission. In the proposed method, the receive filter (i.e., the sample covariance matrix) is estimated using the received samples from the data transmission without using an interference training period. A channel estimation algorithm to use the most reliable data symbols as virtual pilots is employed to improve quality of the channel estimate. Simulation results verify that the proposed receiver algorithms enhance the reception quality of the short packet transmission.

Packet Structure and Receiver Design for Low Latency Wireless Communications With Ultra-Short Packets

Block Diagonalization (BD) algorithm is a generalization of channel inversion scheme in multiuser multi-input multi-output (MIMO) broadcast channels. Although the BD algorithm is effective in removing interuser interference, it has a drawback that additional information should be delivered to the receiver. Recent work on BD with vector perturbation (VP) avoids the need for additional information and hence reduces receiver complexity. In this paper, we propose a method achieving further gain in the BD for multiuser MIMO downlink. By combining the BD and minimum mean square error vector precoding (MMSEVP), we pursue the balance between the interference suppression and the noise enhancement control, resulting in considerable improvement in the effective SINR. In fact, simulation results on the realistic multiuser downlink scenario show that the proposed method brings substantial performance gain over existing multiuser MIMO algorithms (BD, BD-VP and BD-WF).

A MMSE Vector Precoding with Block Diagonalization for Multiuser MIMO Downlink

Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the basestation. Although transmit-side channel state information (CSI) can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user to the basestation is required for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), groups antenna elements using pre-designed patterns. The proposed method introduces the concept of using a header of overall feedback resources to select a suitable group pattern and the payload to quantize the effective channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach.

Antenna grouping based feedback reduction for FDD-based massive MIMO systems

Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multi-input multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (MMSE-VP) for achieving further gain in performance with minimal computational overhead. Two key ingredients to make our approach effective are the QR decomposition based block diagonalization and joint optimization of transmitter and receiver parameters in the MMSE sense. In fact, by optimizing precoded signal vector and perturbation vector in the transmitter and receiver jointly, we pursue an optimal balance between the residual interference mitigation and the noise enhancement suppression. From the sum rate analysis as well as the bit error rate simulations (both uncoded and coded cases) in realistic multiuser MIMO downlink, we show that the proposed BD-MVP brings substantial performance gain over existing multiuser MIMO algorithms.

In this paper, we propose a temporal diversity scheme based on the vector perturbation for a multiuser multipleinput multiple-output (MIMO) broadcasting system. Our method is inspired by the fact that precoding process of the vector perturbation designed to suppress the multiuser interference causes a reduction of the transmitted signal power. In order to boost up the transmit power, we employ a non-integer based vector perturbation together with temporal transmit diversity. We show from the simulation on 10×10 multiuser MIMO system that the proposed method outperforms the epetition coded vector perturbation scheme as well as the standard vector perturbation.

A Temporal Diversity using Vector Perturbation

In this paper, we propose a transmit diversity scheme based on the vector perturbation for a multiuser multiple-input multiple-output (MIMO) broadcasting system. Our method is inspired by the fact that precoding process of the vector perturbation designed to suppress the multiuser interference causes a reduction of the transmitted signal power. In order to boost up the transmit power, we employ a non-integer based vector perturbation together with temporal transmit diversity. We show from the simulation on 10×10 multiuser MIMO system with 16-QAM modulation that the proposed method outperforms the repetition scheme as well as the vector perturbation.

Jungyong Park

Papers

A MMSE Vector Precoding with Block Diagonalization for Multiuser MIMO Downlink

A MMSE Vector Precoding with Block Diagonalization for Multiuser MIMO Downlink

A Temporal Diversity using Vector Perturbation

A vector perturbation based transmit diversity scheme for multiuser MIMO systems