A New User Selection Measure in Block Diagonalization Algorithm for Multiuser MIMO Systems

Kudo, Ryuichi; Takatori, Yasushi; Nishimori, Kentaro; Ohta, Akio; Kubota, S.; Mizoguchi, Masahiro

doi:10.1587/transcom.e92.b.3206

Cited by 8 publications

(6 citation statements)

References 23 publications

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“…It is assumed that equal power is allocated to each STA, P = P n , to prevent unfairness in terms of the transmission quality between STAs. For practical use, the pre-coding weight assumed in this paper is calculated by channel inversion based on the ZF [9,10], a low complexity weight calculation method given by:…”

Section: System Modelmentioning

confidence: 99%

“…In the downlink MU-MIMO-OFDM transmission, inter-stream interference (ISI) is mitigated by pre-coding techniques, such as the linear processing approaches, including zero forcing (ZF) and block diagonalization (BD) [9,10], and the non-linear processing approaches, such as Tomlinson-Harashima precoding and vector perturbation [11,12]. Conventional papers assume scenarios where the number of transmit antennas exceeds the total number of receiving antennas.…”

Section: Introductionmentioning

confidence: 99%

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A Receiving Antenna Allocation Scheme for Downlink MU-MIMO-OFDM Transmission

2018

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This paper proposes a novel receiving antenna allocation scheme for downlink multiuser multiple input multiple output orthogonal frequency division multiplexing (MU-MIMO-OFDM) transmission; an access point (AP) simultaneously transmits data frames to a combination of allocated receiving antennas on a subcarrier basis at each station (STA). The proposed scheme combines a limited channel state information (CSI) feedback sequence with a receiving antenna decision method. In the proposed scheme, each STA estimates the channel responses of all receiving antennas by using the training preamble transmitted from an AP, and then feeds the channel response of the antenna with maximum norm back to the AP when the spatial correlation value between receiving antennas is higher than a threshold. Otherwise, each STA feeds full channel responses back to the AP. This scheme decreases the amount of CSI fed back while exploiting the spatial diversity gain, and the AP’s computational complexity is also decreased regarding the antenna allocation. Moreover, the receiving antenna decision method eliminates the overhead to notify the allocated antenna information from the AP to each STA by simply comparing its own receiving antenna powers. We clarify the effectiveness of the proposed scheme in our computer simulations using channel responses measured in an indoor environment. The results show that the proposed scheme maintains the channel capacity of the downlink MU-MIMO-OFDM transmission while greatly reducing the overhead and computational complexity.

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Receiving Antenna Allocation Scheme for Downlink MU-MIMO-OFDM Transmission

2018

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“…5(b), e.g., users 1 and 3 or users 2 and 3 are selected. As specific algorithm, several methods have been proposed [52]- [55]. Figure 6 shows the effectiveness of user scheduling for MU-MIMO transmission.…”

Section: User Scheduling and Nonlinear Precodingmentioning

confidence: 99%

Survey of Transmission Methods and Efficiency Using MIMO Technologies for Wireless LAN Systems

Hiraguri

Nishimori

2015

IEICE Trans. Commun.

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SUMMARY Multiple-input multiple-output (MIMO) transmission is attracting interest for increasing the transmission rates of wireless systems. This paper surveys MIMO transmission technology from the viewpoints of transmission methods, access control schemes, and total transmission efficiency. We consider wireless local area networks (WLAN) systems that use MIMO technology; moreover, we focus on multiuser MIMO (MU-MIMO) technology, which will be introduced in next-generation WLAN systems such as IEEE802.11ac. This paper explains the differences in the detailed access control procedures for MIMO and MU-MIMO transmission, including channel state information (CSI) acquisition. Furthermore, the issues related to CSI feedback and solutions are also discussed. Related works on the medium access control (MAC) protocol in MIMO/MU-MIMO transmission are introduced. In addition, the throughput performance using MIMO/MU-MIMO transmission is evaluated considering an IEEE802.11ac-based WLAN system. From the numerical evaluation, it is shown that the overhead due to CSI feedback from the user terminals to the base station causes a decrease in the throughput. We verified that implicit beamforming, which eliminates CSI feedback, is effective for solving this issue. , and commercial products based on these standards will appear in the near future. Moreover, the standardization of next-generation wireless LAN (WLAN) aims to achieve further high performance and high efficiency by using MU-MIMO transmission technology, and a task group for that standard called IEEE802.11ax [22] [32]. However, the transmission rate achieved by SU-MIMO/MU-MIMO transmission is not currently adequately utilized because the overhead of the access control protocol in the medium access control (MAC) layer decreases the transmission efficiency, even though the physical transmission rate has been increased in the PHY layer by the adoption of SU-MIMO/MU-MIMO technology. Therefore, the MAC-service access point (MAC-SAP) throughput including the protocol in the MAC layer decreases greatly creases in multilevel modulation and the number of subcarriers in WLAN systems. The decrease in the transmission efficiency is a significant issue because the ratio of the overhead of the MAC protocol is larger for MU-MIMO transmission. Although there are above issues, the frequency utilization and channel capacity have been evaluated in only PHY-layer.Further, the throughput and delay characteristics in relation to the access control scheme have been evaluated in the MAC layer. Therefore, these studies have been individually evaluated. No adequate evaluation of the throughput and transmission efficiency considering both the PHY and MAC layers has not been published.This paper surveys conventional SU-MIMO/MU-MIMO transmission technology from the viewpoints of both wireless communication systems and transmission efficiency, and the most popular WLAN systems that use SU-MIMO/MU-MIMO technology are chiefly discussed. Moreover, we survey the MU-MIMO technology used in next-generatio...

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“…To show the effectiveness of the transmission for each user with the proposed user selection, the improvement rates of the subsets that selected by round-robin selection and the conventional scheme are plotted. In round-robin selection, the subset that maximizes the sum rate in (10) is selected from among all combinations of N s in (12). As the conventional scheme, the user selection algorithm using channel capacity in [8] is compared.…”

Section: A Channel Modelmentioning

confidence: 99%

“…The improvement rate of the selected STA is calculated using the right singular vectors of the channel matrices as shown in [12]. Although the user selection method in [12] needs to fix the number of the spatially multiplexed STAs, the proposed scheme in this paper can determine the number of supported STAs. This approach prevents the AP from consistently selecting the high SNR STA and so offers better fairness.…”

Section: Introductionmentioning

confidence: 99%

User Selection for Multiuser MIMO Systems Based on Block Diagonalization in Wide-Range SNR Environment

Kudo

Takatori

Murakami

et al. 2011

2011 IEEE International Conference on Communications (ICC)

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Multiuser (MU) -multiple input multiple output (MIMO) techniques are attractive to increase the downlink spectrum efficiency since they can accept a small number of antennas at each user station (STA). In MU-MIMO systems, the transmission performance is affected by the STA combination that is spatially multiplexed in the same frequency and same time slot. Thus, the AP needs to determine the optimum STA subset and the number of spatially multiplexed STAs from the channel state information. In this paper, we propose a user selection scheme that uses an iterative algorithm to determine the number and the optimal combination of multiplexed STAs. The proposed scheme chooses STAs one by one so as to improve the throughput of all STAs in the subset compared to that achieved in single-user MIMO transmission. Thus, all STAs have a fair chance of being selected even when their SNRs vary widely. Furthermore, the iterative algorithm has lower calculation complexity than the exhaustive search approach. The index employed for user selection is also simplified by using the signal-space vectors of the channel matrices. Computer simulations confirm that the proposed method improves the increase in STA throughput over single-user MIMO throughput in a wide-range of SNR values while equalizing STA selection probabilities.

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A New User Selection Measure in Block Diagonalization Algorithm for Multiuser MIMO Systems

Cited by 8 publications

References 23 publications

A Receiving Antenna Allocation Scheme for Downlink MU-MIMO-OFDM Transmission

A Receiving Antenna Allocation Scheme for Downlink MU-MIMO-OFDM Transmission

Survey of Transmission Methods and Efficiency Using MIMO Technologies for Wireless LAN Systems

User Selection for Multiuser MIMO Systems Based on Block Diagonalization in Wide-Range SNR Environment

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