Hyun-Myung Kim

Improved Network-Coded Cooperative Transmission with Low-Complexity Adaptation to Wireless Channels

The relay employs network coding to transmit the packets from the source nodes simultaneously, for increasing spectral efficiency in wireless environments. The cooperative transmission based on network coding usually works on decode-and-forward (DF) protocols. However, detection errors at the relay cause error propagation, which degrades the performance of cooperative communications. To overcome this problem, we model the error propagation effect of the DF-based system at the destination as the addition of virtual noise, and then design a low complexity detection method. We derive the achievable diversity gain to evaluate the proposed model and corresponding detection scheme. To extend the proposed model to network-coded systems, we first express the channel conditions between the sources and relay as a single equivalent channel gain. Then, we develop low complexity detection schemes for the network-coded systems. From the error propagation model, we propose a dual mode network coding technique, which exploits different network coding schemes adaptively according to channel qualities. Simulation results show that the proposed model and detection scheme effectively reduce the error propagation effects. Also, the proposed dual mode network coding has gains for all channel conditions and thus gives better BER performance than conventional methods.

Iterative Channel Estimation with Frequency Replacement for SC-FDMA Systems

Single-carrier frequency division multiple access (SC-FDMA) is an attractive air interface scheme for broadband wireless communications. For the coherent demodulation of SC-FDMA systems, the receiver performs channel estimation to obtain the channel frequency response by using the reference signals multiplexed in the transmitted signal. In this paper, we propose an iterative frequency domain channel estimation scheme for SC-FDMA systems. To prevent severe noise enhancements due to the Gaussianity of the frequency domain data signal, we consider two low complexity algorithms, namely, hard and soft frequency replacements. We first analytically derive the mean square error (MSE) to characterize the effects of frequency replacement and post iterative filtering. By analyzing MSE performance, we present a design framework to develop the optimal frequency replacement. Based on the design framework, hard and soft frequency replacement algorithms are optimized in the MSE sense. Then, their low complexity adaptation methods are proposed for practical SC-FDMA systems, where the proposed frequency replacement is performed according to the reliability of the data estimates. Simulation results show that the proposed iterative channel estimation techniques effectively compensate for noise enhancements, and thus give good MSE and frame error rate performances.

Low-Complexity Detection Scheme for Cooperative MIMO Systems With Decode-and-Forward Relays

In this paper, we study low-complexity detection schemes for cooperative multiple-input multiple-output (MIMO) systems with decode-and-forward (DF) relays. In fixed DF protocols, the error propagation effect that limits the diversity gain can be overcome by using joint maximum-likelihood (JML) detection, but its complexity increases exponentially with the number of streams and modulation orders. To develop a low-complexity detection scheme, we first extend the cooperative maximum-ratio combining (C-MRC) scheme to MIMO relay networks, and then investigate the diversity order of the system. We show that C-MRC achieves full diversity gain for orthogonal space-time code, but its diversity gain is limited when the deployed space-time code is non-orthogonal. To address this problem, we propose an effective detection scheme that is applicable to arbitrary space-time codes. On the basis of pairwise error probability approximation, max-log approximation, and the Chernoff bound, we construct an equivalent point-to-point MIMO signal model, and then apply tree-search detection techniques. Compared to JML, the proposed detection scheme significantly reduces the detection complexity while preserving diversity gain. Moreover, it can be readily extended to complex-field network-coding systems whose performance is superior to that of Galois-field network-coding systems. Analysis and simulation results confirm the efficiency of the proposed scheme.

Feedback Optimization Schemes for Downlink MISO-OFDMA Systems With Heterogeneous Users

This paper proposes feedback optimization schemes for multiple-input single-output orthogonal frequency-division multiple access (MISO-OFDMA) systems with heterogeneous users. The proposed scheme adjusts the unit and resolution of the feedback to efficiently exploit the long-term channel statistics, including the path loss, delay spread, and mobility. To develop an analytical optimization framework, we first derive the sum-rate of MISO-OFDMA systems when the channel-state information (CSI) at the transmitter is imperfect because of the quantization error, channel variation, and feedback delay. Based on the derived results, we present effective solutions to the sum-rate maximization problem for distributed and centralized scenarios. When the channel statistics of the users are not available at the base station, each user can improve the sum-rate of the system by minimizing the distortion on CSI feedback under a fixed per-user feedback rate. With the channel statistics of the users, the base station can further control the user set and the feedback rate in addition to the feedback granularity. We evaluate the performance of both distributed and centralized schemes over practical wireless environments, where each user has different long-term channel statistics. Simulation results show that both methods significantly improve the performance of MISO-OFDMA systems.

On the Performance Analysis of MISO Broadcast Channels with Spatial Heterogeneity

We consider the sum-rate performance of multiple-input/single-output broadcast channels in which each user has a different average signal-to-noise ratio (SNR) corresponding to their distance from the base station. Although there are already studies investigating the sum-rate growth under this channel assumption, their proofs are limited to the cases where the pathloss exponent is equal to one or two. However, the pathloss exponent is greater than two in realistic wireless environments. Therefore, by deriving the cumulative distribution function of the channel gain, which differs from the previous results, we can provide an asymptotic sum-rate and a general proof for the sum-rate growth regardless of the value of the pathloss exponent.

Decision-directed channel estimation for SC-FDE in amplify-and-forward relaying networks

In this letter, we propose a decision-directed channel estimation scheme for single-carrier frequency-domain equalization in amplify-and-forward (AF) relaying networks. For coherent combining of the received signals in AF-based cooperation, conventional channel estimation schemes have focused on estimation of source-destination and source-relay-destination channels. However, if the individual channels in the source-relay-destination link are not considered, the relaying gain is limited because the noise propagation from the relay to the destination affects the effective signal-to-noise ratio at the destination. The proposed scheme estimates the effective channel parameters for maximal-ratio combining, in the absence of channel-state information (CSI) from the relay. Simulation results show that the proposed scheme outperforms the conventional scheme and approaches the performance with perfect CSI.

Improved Spectrum-Sharing Protocol for Cognitive Radio Networks With Multiuser Cooperation

This paper proposes an improved spectrum-sharing protocol for multiuser cooperation in cognitive radio (CR) networks. In CR networks, a secondary user (SU) can access the licensed bands of a primary user (PU) as compensation for cooperative transmission. During cooperative transmission, the SU concurrently transmits its own signal and network-coded signal from the PUs. However, detection errors at the SU cause error propagation which degrades the performance of the PU and SU. To address this problem, we develop a cooperative maximal-ratio combining scheme that mitigates the error propagation and achieves diversity gain. To evaluate the combining scheme, we derive a diversity order and closed-form bit error rate (BER) expression for arbitrary M-QAM at high SNR. The analysis results show that the diversity order and BER depend on the fraction of the transmit power at the SU. Based on the dependency of the fraction factor, we propose an optimization problem to minimize the BER of the SU while guaranteeing the PUs BER. Further, we apply the BER-constrained optimization problem to the adaptive modulation system. Simulation results show that the proposed cooperation provides full diversity gain to the PU and thus improves its spectral efficiency by using the optimized fraction factor.

Frequency domain channel estimation for MIMO SC-FDMA systems with CDM pilots

In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.

Time-Domain Differential Feedback for Massive MISO-OFDM Systems in Correlated Channels

Massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) is a promising technology for next-generation wireless communications. However, when channel state information (CSI) at the transmitter is obtained using channel feedback, the benefits of this system are severely limited by the tradeoff between downlink capacity and feedback overhead. To solve this problem, we propose a time-domain differential feedback scheme for massive multiple-input single-output (MISO) OFDM systems. The proposed scheme exploits channel correlations in time, frequency, and space domains simultaneously by considering differential channel impulse response (CIR). To simplify the codebook design, and to reduce codeword-search complexity, we partition and then quantize the differential CIR using a number of subcodebooks. Because the total feedback bits are shared by the subcodebooks, we further optimize the bit allocation for them to minimize the total quantization error. For this, we analyze the quantization error of the proposed scheme and then use the analysis results for the bit-allocation optimization. In simulations, the proposed scheme efficiently exploits all correlations and achieves significant spectral-efficiency gain compared to conventional feedback schemes.

Feedback granularity control for multiuser MIMO-OFDMA systems

In this paper, we propose a feedback granularity control scheme for multiuser multiple-input multiple-output orthogonal frequency-division multiple access (MIMO-OFDMA) systems. The proposed scheme resizes the unit and the resolution of the feedback to efficiently exploit channel correlations in both the time and the frequency domains. Two types (centralized and distributed) of granularity search methods are proposed, and their performance characteristics over practical wireless channels are investigated. Simulation results show that the proposed schemes (particularly the distributed method) effectively calculate the optimal granularity, and thus significantly improve the sum-rate of multiuser MIMO-OFDMA systems.