Minjoon Kim

A high performance MIMO detection algorithm for DL MU-MIMO with practical errors in IEEE 802.11ac systems

In this paper, we propose a high performance multiple-input and multiple-output (MIMO) detection algorithm for downlink multiuser MIMO (DL MU-MIMO) with practical errors in IEEE 802.11ac systems. The DL MU-MIMO system using the precoding matrix, which is generated through imperfect channel state information caused by channel estimation error and channel feedback quantization error, has severe performance degradation since each station (STA) receives the desired signal for the STA as well as the interference signal for different STAs. Therefore, the proposed detection algorithm is developed by considering both the desired signal and the interference signal. Using the characteristics of the interference signal, the proposed detection algorithm is performed by additionally detecting several interference symbols. The proposed algorithm has better performance than the conventional algorithm considering only the desired signal. Simulation results show that the coded bit error rate performance of the proposed algorithm was improved in all modulation and coding scheme cases, compared to the conventional algorithm.

Low-complexity MIMO detection algorithm with adaptive interference mitigation in DL MU-MIMO systems with quantization error

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complex MIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

Exact ML Criterion Based on Semidefinite Relaxation for MIMO Systems

In this letter, we propose an exact maximum likelihood (ML) criterion based on semidefinite relaxation (SDR) in multiple-input multiple-output systems. Although a conventional SDR criterion for determining whether a symbol is the ML solution exists, its results cannot be guaranteed when noise is present. In place of the conventional criterions positive semidefinite (PSD) discriminant, we propose a new, exact ML criterion based on the condition that all diagonal values are positive (PDV), a simple characteristic and necessary condition of PSD. The proposed criterion has a lower calculation complexity for testing than does a PSD and can ensure that the ML solution is always satisfactory.

Lattice-Reduction-Aided Partial Marginalization for Soft Output MIMO Detector With Fixed and Reduced Complexity

In this letter, we propose lattice-reduction (LR)-aided partial marginalization (PM) for soft output multiple-input multiple-output (MIMO) detection. PM has the advantages of a fully predictable runtime and convenience in parallelization while offering a well-defined tradeoff between the performance and the computational complexity. However, the computational complexity of PM to achieve a high level of performance is considerably high. In order to reduce the complexity of PM, the proposed scheme performs low-complexity LR-aided marginalization instead of exact marginalization (EM) to avoid the exhaustive approach of the EM, which mainly increases the overall complexity. The experimental results demonstrate that the computational complexity of the proposed scheme is considerably lower with negligible performance degradation compared to conventional PM.

A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection

In this paper, we propose a fixed-complexity variant of LLL (Lenstra-Lenstra-Lovasz) algorithm. LLL algorithm is widely used in MIMO signal processing to obtain full diversity gain with low complexity increase. However, because of its non-deterministic nature with varying complexity and high worst-case costs, the real implementation of original LLL algorithm is difficult. Although some fixed-complexity variants of LLL algorithm has been proposed, but still their complexity in large MIMO system is high. The proposed algorithm uses column selection method based on threshold which leads to the fast convergence in fewer iterations. Simulation result shows that the proposed algorithm converges faster than other fixed-complexity variants of LLL algorithms while it saves about 30% complexity in 8 × 8 MIMO system compared to existing fixed-complexity LLL (fc-LLL) algorithm.

Adaptive interference-aware receiver for multi-user MIMO downlink in IEEE 802.11ac

In multi-user MIMO downlink system, a receiver suffers from interferences because precoding technique cannot be perfectly performed. In this paper, we propose an adaptive interference-aware receiver choosing interference whitening or interference detection based on the channel state. The proposed scheme can achieve the near optimal performance with low computational complexity.

High reliable broadcasting protocol in WLAN using retransmission

In this paper, high reliable broadcasting protocol in WLAN using retransmission is proposed. Broadcast in conventional WLAN has advantage of high efficient use of wireless resource, but has disadvantage of low reliability and data rate. Broadcasting frame includes the sequence indicating which nodes send ACK frame first. If some nodes fail to receive the frame, the node which success to receive the frame retransmits the frame with broadcasting. By these broadcasting with relay retransmission algorithm, the probability of transmission increase when the channel is better between the nodes.

Design of 270 Mbps 2×2 MIMO-OFDM system for video streaming in internet of things

This paper presents designing of wireless local area network (WLAN) modem for video streaming in internet of things (IoT). Many concepts based on video streaming are introduced recently, and these systems need communication modem supporting high throughput for transmission of high quality of video. In this paper, WLAN modem using 2×2 multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technique is designed. The proposed WLAN modem can support max 270 Mbps.

Extended version of sphere decoding with MMSE based enumeration for DL MU-MIMO systems

In this paper, we propose an extended version of sphere decoder (ESD) with the MMSE based enumeration for DL MU-MIMO systems. In previous work, we proposed the ESD which detects interference signals additionally. The ESD can achieve near-optimal performance, but it has much higher complexity than the existing SD. Therefore, this paper presents the improved enumeration based on MMSE. The proposed algorithm can reduce the complexity of ESD significantly while having low performance degradation.

Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems

In previous work, we proposed the positive diagonal values (PDV) criterion, which is an exact-ML criterion of semidefinite relaxation (SDR) optimality condition. In this paper, we apply the PDV criterion to the tree-searching based MIMO detection by two ways. The first application is node-pruning algorithm for depth first search such as sphere decoding (SD). The proposed node-pruning algorithm using PDV criterion is not based on the Euclidean distance mostly used for node-pruning algorithm, instead, it uses an absolute test in each node so that it can be worked independently with many existing node-pruning algorithms. Furthermore, the proposed node-pruning algorithm can guarantee the exact-ML performance and reduce the number of nodes visited significantly. The second application is K-best algorithm of breadth first search. The proposed K-best algorithm takes K candidates at each stage based on PDV criterion. As a result, the proposed K-best algorithm can achieve near-ML performance.