• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.12A
• /
• pp.1182-1188
• /
• 2006

Adaptive OFDM(Orthogonal Frequency Division Multiplexing) improves data capacity and system performance over multipath fading by adaptively changing modulation schemes according to channel state information(CSI). To achieve a good performance in adaptive OFDM systems, CSI should be transmitted from receiver to transmitter in real time through feedback channel. However, practically, the CSI feedback delay d which is the sum of the data processing delay and the propagation delay is not negligible and damages to the reliability of CSI such that the performance of adaptive OFDM is degraded. This paper presents an adaptive OFDM system with a multistep predictor on the frequency axis to effectively compensate the multiple feedback delays $d(\geq2)$. Via computer simulation we compare the proposed scheme and existing adaptive OFDM schemes with respect to data capacity and system performance.

• Journal of Communications and Networks
• /
• v.15 no.4
• /
• pp.352-361
• /
• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.2
• /
• pp.593-609
• /
• 2012

We propose a scheme to reduce the overhead associated with channel state information (CSI) feedback required for opportunistic scheduling in wireless access networks. We study the case where CSI is partially overheard by mobiles and thus one can suppress transmitting CSI reports for time varying channels of inferior quality. We model the mechanism of feedback suppression as a Bayesian network, and show that the problem of minimizing the average feedback overhead is NP-hard. To deal with hardness of the problem we identify a class of feedback suppression structures which allow efficient computation of the cost. Leveraging such structures we propose an algorithm which not only captures the essence of seemingly complex overhearing relations among mobiles, but also provides a simple estimate of the cost incurred by a suppression structure. Simulation results are provided to demonstrate the improvements offered by the proposed scheme, e.g., a savings of 63-83% depending on the network size.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.7A
• /
• pp.762-769
• /
• 2007

Adaptive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system adaptively changes modulation scheme depending on feedback channel state information (CSI). The CSI feedback channel which is the reverse link channel has multiple symbol delays including propagation delay, processing delay, frame delay, etc. The unreliable CSI due to feedback delay degrades adaptive modulation system performance. This paper compares the MSE and data capacity with respect to delay and channel signal to noise ratio for the two multi-step channel prediction schemes, CTSBP and BTSBP, such that robust adaptive SISO-OFDM/MIMO-OFDM is designed over severe mobile multipath channel conditions. This paper presents an interpolation method to reduce feedback overhead for adaptive MIMO-OFDM and shows MSE with respect to interpolation interval.

• Journal of Communications and Networks
• /
• v.18 no.1
• /
• pp.95-104
• /
• 2016

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

• Journal of Advanced Information Technology and Convergence
• /
• v.9 no.2
• /
• pp.1-14
• /
• 2019

This paper considers a multiple-input multiple-output (MIMO) power line communication (PLC) network where interference alignment (IA) technique is used to mitigate the interference that arises in multi-user networks. IA as a precoding technique requires perfect channel state information (CSI) to achieve maximum multiplexing gain. Due to the common-mode reception at the receiver ports, we assume imperfect CSI for the IA precoding design. Here, the CSI is quantized and sent via feedback to the transmit ports. For different levels of CSI quantization, we evaluate the performance of various IA algorithms via Monte Carlo simulations. Simulation results reveal the superior performance of the proposed scheme due to common-mode reception in IA MIMO PLC networks. It is shown that for a quantization level of 5 bits, the CM reception improves the sum-rate by up to 70%.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.213-214
• /
• 2006

To reduce the feedback overhead of predicted CSI (channel status information) of adaptive OFDM (orthogonal frequency division multiplexing), we use partial data of CSI and employ linear interpolation. Simulation results show estimated CSI and its MSE.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.11
• /
• pp.5304-5322
• /
• 2018

Since designing a feedback topology is a practical way to implement interference alignment at reduced cost of channel state information (CSI) feedback, six feedback topologies have been presented in prior works for a K-user multiple-input multiple-output interference channel. To fully reveal the potential benefits of the feedback topology in terms of the saving of CSI overhead, we propose a new feedback topology in this paper. By efficiently performing dimensionality-decreasing at the transmitter side and aligning interference signals at a subset of receivers, we show that the proposed feedback topology obtains substantial reduction of feedback cost over the existing six feedback designs under the same antenna configuration.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.4
• /
• pp.628-636
• /
• 2015

In this paper, we propose a non-convex compressed sensing(NCCS)-based channel state information(CSI) feedback scheme for massive multiple-input multiple-output(MIMO) systems. Combining the random vector quantization(RVQ), the proposed scheme permits a transmitter to obtain CSI with acceptable accuracy under substantially reduced feedback load. Furthermore, it recovers CSI from fewer measurements than that of existing convex compressed sensing(CCS)-based schemes even if the measurements are inaccurate and incomplete. Simulation results show that the proposed scheme achieves higher throughput than both existing CCS-based feedback scheme and random vector quantization(RVQ) feedback scheme with the same feedback load.

• Journal of Communications and Networks
• /
• v.16 no.1
• /
• pp.1-9
• /
• 2014

Block diagonalization (BD) has been proposed as a simple and effective technique in multiuser multiple-input multiple-output (MU-MIMO) broadcast channels. However, when channel state information (CSI) knowledge is limited at the transmitter, the performance of the BD may be degraded because inter-user interference cannot be completely eliminated. In this paper, we propose an efficient CSI quantization technique for BD precoded systems with limited feedback where users supported by a base station are selected by dynamic scheduling. First, we express the received signal-to-interference-plus-noise ratio (SINR) when multiple data streams are transmitted to the user, and derive a lower bound expression of the expected received SINR at each user. Then, based on this measure, each user determines its quantized CSI feedback information which maximizes the derived expected SINR, which comprises both the channel direction and the amplitude information. From simulations, we confirm that the proposed SINR-based channel quantization scheme achieves a significant sum rate gain over the conventional method in practical MU-MIMO systems.