Wing Seng Leon

Cyclic Delay Diversity for Single Carrier-Cyclic Prefix Systems

This paper presents the application of cyclic delay diversity (CDD) to block-based single carrier cyclic prefix (SC-CP) systems. It is shown that diversity advantage is achieved even without additional coding due to the inherent cross-tone pre-coding present in SC-CP. We also present a CDD SC-CP transmission system for correlated channels. By using beamforming techniques, virtual uncorrelated channels are created for CDD transmissions. Simulations results show that the proposed schemes provide diversity gain. Furthermore, when beamforming is used together with CDD, array gain is also observed

Design of cyclic delay diversity for single carrier cyclic prefix (SCCP) transmissions with block-iterative GDFE (BI-GDFE) receiver

Single carrier cyclic prefix (SCCP) modulation has been adopted as one of the physical layer air-interfaces for IEEE802.I6 standards due to its less stringent requirement on peak-to-average power ratio (PAPR) than multicarrier modulation. As a single carrier transmission, however, the received SCCP blocks suffer from inter-symbol interference (ISI). The block iterative generalized decision feedback equalizer (BI-GDFE) is an effective interference cancellation scheme which generally shows performance improvement over linear equalizers. However, in order to achieve a significant gain, the channel must contain rich multipath components, and this may not necessarily be true in many systems. In this paper, we propose to apply cyclic delay diversity (CDD) to a SCCP system so that the possible performance improvement by using a BI-GDFE detector can be enhanced. The asymptotic performance of the proposed system is analyzed using random matrix results. We propose a scheme to determine the optimal delay parameter for CDD. Computer simulations have shown that by incorporating CDD into the transmitter and using a BI-GDFE receiver, the BER performance of the system can approach the MFB within several iterations for high SNR region.

A low complexity decoding algorithm for extended turbo product codes

In this letter, we propose a low complexity algorithm for extended turbo product codes by considering both the encoding and decoding aspects. For the encoding part, a new encoding scheme is presented for which the operations of looking up and fetching error patterns are no longer necessary, and thus the lookup table can be omitted. For the decoder, a new algorithm is proposed to extract the extrinsic information and reduce the redundancy. This new algorithm can reduce decoding complexity greatly and enhance the performance of the decoder. Simulation results are presented to show the effectiveness of the proposed scheme.

A New Method for Frequency Offset and Channel Estimation in OFDM

Efficient estimations of the carrier frequency offset (CFO) and channel are vital to orthogonal frequency division multiplexing (OFDM). In this paper, a new method based on limited channel length and null subspace is proposed to estimate the CFO in OFDM. The method needs only one OFDM block (symbol) as pilot. The identifiability of the method is analyzed and requirements for the pilot are found. The same pilot is also used for channel estimation. It is shown that a pilot with constant amplitude and random phases is the best choice for both channel and CFO estimation. Furthermore, an enhanced method is proposed by using multiple receiving antennas. Simulations demonstrate that the proposed methods are effective.

Shortened Turbo Product Codes: Encoding Design and Decoding Algorithm

Shortened turbo product codes (TPCs) have already been adopted in many standards. In this paper, we study shortened TPCs from two aspects, namely encoding design and decoding algorithm. To obtain different encoding block sizes, shortened-extended Hamming codes are used as the component codes of product codes in the IEEE 802.16 standard. To design a good structure for the shortened TPC, we compute the undetected error probability of its corresponding component codes. The component codes are shortened-extended Hamming codes, and their optimal generator polynomials are selected in terms of their undetected error probability. For the decoding algorithm, we present an efficient Chase decoding algorithm for shortened TPCs in flat fading channels. In the proposed scheme, the reliability factor used in Pyndiahs scheme is not needed; thus, the decoding complexity is greatly reduced by avoiding the normalization operation of the whole code word at each iteration. Simulation results are also presented to verify the performance of the proposed algorithm.

Dynamic QRDM Receivers for MIMO Beamforming Systems with Imperfect Channel State Information

For multiple-input multiple-output (MIMO) antenna systems, if perfect channel state information (CSI) is available at the transmitter and receiver sides, advanced beamforming (ABF) can be applied at both sides so that the transmitted data streams can be decoupled easily, and adaptive modulation can be utilized to maximize the throughput. When the available CSI is imperfect, however, the data streams cannot be decoupled completely with linear receive beamforming. In this paper, a dynamic QR decomposition based M-Algorithm (QRDM receiver) is proposed for recovering the data streams delivered by MIMO beamforming systems with adaptive modulation designed by imperfect CSI. We also propose a scheme to determine the decoding order for assisting the QRDM operation. The proposed schemes can also be applied to multiuser MIMO systems with random transmit beamforming where the random beams are hardly match the desired users CSI exactly. Computer simulations have shown that the proposed receiver is very robust to the CSI mismatch as compared to conventional linear receivers

Frequency Domain Equalization and Interference Cancellation for TD-SCDMA Downlink in Fast Time-Varying Environments

In time division synchronous code division multiple access downlink, one computationally efficient receiver for fast time-varying environments is the subblock processing receiver, which utilizes overlap-save fast Fourier transform. In this paper, we first analyze the interferences involved with the subblock processing method proposed by Held and Kerroum and then propose a new subblock processing receiver for fast time-varying channels. The proposed receiver consists of two stages. In the first stage, the entire received chip block is partitioned into overlapping subblocks and they are individually equalized and despread. We then artificially generate the interferences caused by adjacent blocks and the unwanted chip interference within the same subblock and eliminate them from the received data signals. Then, a second subblock processing is performed to detect the transmitted symbols. A practical channel estimator is also introduced to be used with the proposed receiver. Simulation results have shown that the proposed receiver provides a significant performance improvement as compared with the conventional subblock processing method.

Statistical pre-filtering for OFDM systems with multiple transmit antennas

The incorporation of orthogonal frequency division multiplexing (OFDM) with space-time/frequency coding is a robust and effective method to achieve transmit diversity gain and also suppress both multipath fading and inter-symbol interference for broadband wireless transmissions. This paper is concerned with downlink performance improvement using multiple transmit antennas for OFDM systems with large delay spread. We propose a delay spread reduction method using space frequency block coding and statistical pre-filtering, which combines signal pre-alignment and multiple transmit beamformers, designed with the statistical knowledge of downlink channel state information. The proposed method transforms a large delay spread channel into multiple channels with small delay spread, thus not only shortening the required cyclic prefix length, but also maintaining path diversity by the use of space-frequency coding. By computer simulations we evaluated the effectiveness of the proposed method.

The polynomial-based generalized least mean squares estimator for Rician and Rayleigh fading channels

A simplification of a previously developed polynomial-based generalized recursive least squares estimator for fading channels is presented. The instantaneous inverse correlation matrix, required for each iteration of the original algorithm, is replaced by a time-invariant approximation to reduce the computational complexity. Under some conditions, the simplified algorithm is equivalent to the standard least mean squares algorithm and is thus called the polynomial-based generalized least mean squares channel estimator. Like its predecessor, it employs polynomial channel models and does not require a priori knowledge of the channel statistics. Furthermore, the proposed estimator does not need to be augmented to accommodate channels with a non-fading mean component. Therefore unlike statistical approaches such as Kalman filtering, the polynomial-based generalized least mean squares estimator is applicable to both Rician and Rayleigh channels without any re-configuration and increased complexity. Simulated and analytical results illustrate its tracking performance and the improvement over the standard least mean squares algorithm.

Multiple Frequency Offset Estimations in Multiuser OFDMA

In multiuser OFDMA uplink, different users usually have different carrier frequency offsets (CFOs). Estimation of these multiple CFOs is a crucial and challenging task. In this paper, a dedicated pilot OFDM symbol is designed to estimate the CFOs. Based on the maximum likelihood (ML) principle, a method is derived to estimate the CFOs of all users by optimizing a multi-dimensional (MD) cost function. To reduce complexity, the MD optimization problem is turned into independent one-dimensional (ID) optimization problems based on a specially designed pilot OFDM symbol. It is proved that the CFOs are identifiable by optimizing the ID cost functions. Although the ID optimization is substantially simpler than the MD optimization, it may still be vulnerable to local minima/maxima and sometimes too complex for wireless applications. A fast algorithm is then derived, which finds the CFOs in closed forms and needs very low computational complexity.