Keying Wu

Single-symbol preamble design and channel estimation for filter bank multi-carrier modulations

In this paper, the channel estimation related issues in FBMC systems are discussed. A single-symbol preamble structure is proposed and the corresponding channel estimation methods are provided for filter bank multicarrier (FBMC) systems. The simulation results show that compared with the existing methods, the proposed scheme achieves impressive performance gains (up to 4.0dB) with much smaller preamble resource overhead. This is obtained through effective channel filtering for the intrinsic imaginary interference and additive noise exploiting the sparse property of the channel response in delay domain. With the proposed solution, the FBMC system can even save half resources for pilots compared with OFDM systems.

Compressive sensing of digital sparse signals

This paper discusses compressive sensing with digital sparse signals. The motivation is that most existing sparse signal recovery algorithms, like matching pursuit, convex relaxation and Bayesian framework, do not fully exploit the digital nature of signals when dealing with digital sparse signals, which result in certain performance losses. In this paper, we solve this problem via a permutation-based multi-dimensional sensing matrix and an iterative recovery algorithm with maximum likelihood (ML) local detectors. The sensing matrix considered consists of several sub-matrices, each composed of a random permutation matrix and a block-diagonal matrix. The measurements generated from the same permutation matrix are referred to as a dimension. The block-diagonal matrices allow the use of the low-complexity ML detector in each dimension, which best utilizes the digital nature of signals. The multi-dimensional structure of the sensing matrix enables information exchange between dimensions through an iterative process to achieve a near global-optimal estimation. Numerical results are used to show the rate-distortion performance of the proposed technique. It is shown that it can achieve much better rate-distortion than the existing approaches based on convex relaxation and Bayesian framework with digital source signals.

Uplink multi-BS MIMO with limited backhaul bandwidth 1

Uplink collaborative multiple-input-multiple-output (MIMO) processing among multiple base stations (BSs), also known as uplink multi-BS MIMO, is an effective way to solve the inter-cell interference in cellular systems. However, the significantly increased overhead on the backhaul network due to inter-BS information exchange has seriously restricted its application in practical systems with limited backhaul bandwidth. In this paper, we propose a three-stage technique for inter-BS information exchange in uplink multi-BS MIMO. A sub-optimal coordinated detection algorithm based on soft combining is considered to compromise between the performance and overhead. The major improvement over the existing solutions is that the proposed technique utilizes one property of soft combining to reduce the backhaul overhead: soft information combination is only needed for a very small part of the information bits that have mismatched local decoding results in different BSs. A three-stage information exchange technique is proposed to utilize this property, which allows the BSs to first locate the bits that need soft information combination and then exchange soft information for these bits only. By doing so, the backhaul overhead can be greatly reduced without performance degradation. Both simulation results and overhead analysis are used to demonstrate the benefit of the proposed technique. Comparisons with other coordinated detection algorithms like optimal joint detection and distributed interference cancellation show that it can provide a better tradeoff between the performance and overhead. 1

Scalable Limited Channel Feedback for Downlink Coordinated Multi-Cell Transmission

It is well known that coordinated multi-cell transmission in downlink (DL) is a promising technique to significantly increase the system throughput and cell-edge user throughput. In this paper, we propose a scalable two-stage channel feedback mechanism not only to support downlink single-cell multi-user MIMO (MU-MIMO), but also to efficiently support multi-cell coordination. This scheme yields remarkable system performance improvements with considerable uplink (UL) feedback overhead, and also has good backward compatibility for single-cell transmission scheme.

Mutual coupling cancelation for compact transmit antenna arrays

Mutual coupling between elements in compact transmit antenna arrays is taken into account in performance prediction and system design of multiple-input multi-output (MIMO) systems. The transmitter-end coupling matrix comprised of array impedance matrix and effective load impedance matrix is derived. The impact of transmitter-end mutual coupling on spatial correlation, radiated power, and system capacity is studied. It is shown that for MIMO systems with compact transmit antenna arrays, transmitter-end mutual coupling seriously degrades system capacity. To mitigate the capacity degradation, a simple transmitter-end coupling cancelation method is proposed. It is shown through numerical experiments that the proposed method can significantly improve system capacity in the case that transmit antennas are placed closely.

On the Feedback Enhancement and System Performance Evaluation of Downlink MU-MIMO for 3GPP LTE-Advanced

The feedback accuracy for the multiuser multiple input multiple output (MU-MUMO) system is to be enhanced in the release 10 of 3GPP LTE specification. In this paper, we propose a feedback mechanism together with associated precoding and scheduling schemes that could improve the feedback accuracy for both single user (SU) and multiuser MIMO. System level simulation results of the proposed scheme are evaluated and compared with the baseline of LTE Release 8 MU-MIMO. Results show that with a small amount of extra overhead, the proposed scheme can outperform Release 8 MU-MIMO by at least 10%.

An efficient algorithm for partial interference cancellation group decoding

This paper presents an efficient algorithm for the partial interference cancellation (PIC) group decoding. Partial interference cancellation is a linear operation that cancels interferences among symbol groups. The basic algorithm for the PIC operation requires a lot of matrix multiplications and inversions. Even though these matrix operations can be done in an efficient way by taking advantage of the Hermitian property, the computational burden is still high and may not always be acceptable. We propose a new algorithm for the PIC operation which requires much less and simpler matrix operations. The new algorithm significantly reduces the computational complexity of the PIC operation by one order of magnitude.

Multi-cell hybrid channel information feedback for downlink multi-cell precoding

A multi-cell hybrid channel state information (CSI) feedback scheme was proposed, which has an ideal nested hierarchical structure to support not only the advanced multi-cell MIMO precoding, but also the traditional single-cell single-user and multi-user precoding transmissions. A quantization scheme for the multi-cell hybrid CSI feedback was provided, using codebook based vector-quantization for the per-cell CSI information part and scalar-quantization for the inter-cell CSI information part. The hierarchical structure of the multi-cell hybrid CSI feedback simplifies greatly the feedback signaling design, and implicitly supports the dynamic switch between different operation modes. Simulation results show that the proposed CSI feedback solution can enable efficient DL single-cell and multi-cell precoding transmissions.

A Novel Double-Polarized SFBC-OFDM Scheme for ICI Suppression

MIMO-OFDM is widely considered as a promising framework of the future broadband mobile communication systems due to its prominent advantages such as high spectral efficiency, low-complexity equalization for multi-path fading, and sufficient exploiting of the spatial degree of freedom. However, an inherent drawback of OFDM, i.e., high sensitivity to frequency offset, limits the application scenarios of MIMO-OFDM significantly. This paper proposes an enhanced MIMO-OFDM scheme, termed double-polarized SFBC-OFDM (DP-SFBC-OFDM), which can improve the robustness to frequency offset with only very low complexity increase at the receiver. Simulation results show that even for very large frequency offset, the system only has limited performance degradation (e.g., normalized frequency offset of 0.4 only lead to performance loss of smaller than 1dB for 64QAM for the proposed scheme while ordinary transmission scheme totally collapse in this case).

A Cross-Designed V-Blast Code Robust to Channel Correlation

The vertical Bell laboratory layered space-time (V-BLAST) code transmits independent data streams from each transmit antenna, and it may perform poorly over spatially correlated channels. To overcome this drawback, we present in this paper a cross-designed V-BLAST code, each component of which is, like a linear dispersion code, a combination of several transmitted symbols. Since the new code incorporates the advantages of V-BLAST and linear dispersion codes, it achieves robust performance to spatial correlation with low complexity, full transmission rate, and short decoding delay. Computer simulations demonstrate the efficiency of the proposed code by comparison with the V-BLAST and two typical full-diversity full-rate codes.