Na Yi

Bit and Power Loading for OFDM-Based Three-Node Relaying Communications

Bit and power loading (BPL) techniques have been intensively investigated for the single-link communications. In this paper, we propose a margin-adaptive BPL approach for orthogonal frequency-division multiplexing (OFDM) systems assisted by a single cooperative relay. This orthogonal half-duplex relay operates either in the selection detection-and-forward (SDF) mode or in the amplify-and-forward (AF) mode. Maximum-ratio combining is employed at the destination to attain the achievable distributed spatial diversity-gain. Assuming perfect channel knowledge is available at all nodes, the proposed approach is to minimize the transmit-power consumption at the target throughput (average number of bits/symbol) and the target link performance. With respect to various power-constraint conditions, we investigate two distributed resource-allocation strategies, namely flexible power ratio (FLPR) and fixed power ratio (FIPR). The FLPR strategy is proposed for scenarios without individual local power constraint. The source power and relay power have a flexible ratio for each subcarrier. The FIPR strategy is proposed for scenarios with individual local power constraint. The source power and relay power have a fixed ratio for each subcarrier. Computer simulations are carried out to evaluate the proposed approach with respect to the relay location. Significant performance improvement is observed in terms of both the symbol-error-rate and the transmit-power efficiency.

Underlay Cognitive Radio with Full or Partial Channel Quality Information

Underlay cognitive radios (UCRs) allow a secondary user to enter a primary users spectrum through intelligent utilization of multiuser channel quality information (CQI) and sharing of codebook. The aim of this work is to study two-user Gaussian UCR systems by assuming the full or partial knowledge of multiuser CQI. Key contribution of this work is motivated by the fact that the full knowledge of multiuser CQI is not always available. We first establish a location-aided UCR model where the secondary user is assumed to have partial CQI about the secondary-transmitter to primary-receiver link as well as full CQI about the other links. Then, new UCR approaches are proposed and carefully analyzed in terms of the secondary users achievable rate, denoted by 𝐶2, the capacity penalty to primary user, denoted by Δ𝐶1, and capacity outage probability. Numerical examples are provided to visually compare the performance of UCRs with full knowledge of multiuser CQI and the proposed approaches with partial knowledge of multiuser CQI.

Investigation of using passive repeaters for indoor radio coverage improvement

Recently, the issue of how to improve indoor radio coverage has received considerable attention. In this paper, we investigate radio coverage improvement by using passive repeaters, including both single and multiple repeaters. It is identified that the major function of the passive repeater is to change the field distribution in an indoor environment and therefore to improve the radio coverage over certain (not all) areas, while the overall power within the environment is not changed. The change of the field distribution can generate more uncorrelated signals in the area, which makes antenna diversity systems and MIMO systems more effective.

Channel estimation for PRP-OFDM in slowly time-varying channel: first-order or second-order statistics?

The statistics-based channel estimators can estimate the channel state information (CSI) in the static channel but can only obtain the averaged CSI (ACSI) in the time-varying (TV) channel. This letter investigates both first-order statistics (FOS) and second-order statistics (SOS)-based channel estimators for the pseudo random postfix (PRP) orthogonal frequency-division multiplexing system in the slowly TV channel. It is shown that the FOS-based approach outperforms the SOS-based approaches in the ACSI estimation. Using estimated ACSIs for the channel equalization, simulation results indicate that the SOS-based approaches converge to the FOS-based approach in the high signal-to-noise ratio range.

Joint Rate Adaptation and Best-Relay Selection Using Limited Feedback

This paper presents a novel joint rate adaptation and relay selection scheme for multi-relay networks adopting half-duplex best-relay decode-and-forward protocol. The proposed scheme aims to maximize the overall transmission rate when relays are allowed to forward messages using different rates from the source. It is shown that the proposed scheme outperforms the conventional adaptive scheme in terms of the spectral efficiency (e.g. by 10.1% improvement for SNR=10 dB). Furthermore, in order to reduce signaling overhead of the proposed scheme, a number of joint discrete-rate adaptation and relay selection approaches are proposed for both non-reciprocal and reciprocal channels. The relay selection is basically a two-stage scheme. At the rm first stage, a set of relays are selected based on mixed channel quality information (CQI), i.e., the knowledge of CQI varies for different links; at the second stage, the best relay within the set is selected based on instantaneous CQI, which is obtained through carefully designed signaling protocols. It is shown that the proposed discrete-rate adaptation schemes can offer comparable spectral efficiency to the conventional adaptive scheme with significantly reduced signaling overhead.

Rate-Adaptive Bit and Power Loading for OFDM Based DF Relaying

In this paper, we investigate the adaptive bit and power loading approach for the OFDM-based relaying communications. The relaying protocol is half-duplex outage symbol-level-selection detection-and-forward. The source and the relay has the separate power constraint. The maximum-ratio combining is employed at the destination to achieve the maximum distributed spatial diversity-gain. Assuming the perfect channel knowledge available at all nodes, we propose a sub-optimum rate-adaptive bit and power loading approach to maximize the number of bits/symbol for the target link performance. The proposed approach offers lower complexity for implementation as well as the integer number of bits/symbol. Computer simulations are used to examine the proposed approach for various scenarios with respect to the relay location and the distributed power allocation.

Bit and power loading for OFDM with an amplify-and-forward cooperative relay

In this paper, we propose a rate-adaptive bit and power loading approach for the OFDM-based relaying communications. The cooperative relay operates in the half-duplex amplify-and-forward mode. The source and the relay has the separate power constraints. The maximum-ratio combining is employed at the destination for maximizing the received SNR. Assuming the perfect channel knowledge available at all nodes, the proposed approach is to maximize the throughput (the number of bits/symbol) at the given power constraint and the target link performance. Unlike the water-filling method, the proposed approach does not need the iterative loading process, and can offer the sub-optimum performance. Computer simulations are used to test the proposed approach for various scenarios with respect to the relay location or the distributed power allocation.

Pilot embedded space-time block coded OFDM in unknown multipath fading channel

Space-time coding has been well documented as an attractive means to achieve high data rate transmissions. The paper investigates space-time block coded (STBC) OFDM systems in unknown multipath fading channels using a pilot embedded (PE) technique. The PE technique superimposes periodic training-sequences on information-bearing signals at a low power. There is no loss in information rate. Employing first-order statistics, it enables a closed-form channel estimation algorithm to track slowly time-varying channels. A mean-square-error (MSE) bound is derived to evaluate the proposed channel estimator. Computer simulation examples are presented to demonstrate MSE and overall system performances in the presence of unknown multipath fading channels.

Low-Complexity MU-MIMO Nonlinear Precoding Using Degree-2 Sparse Vector Perturbation

Multiuser multiple-input multiple-output (MUMIMO) nonlinear precoding techniques face the problem of poor computational scalability to the size of the network. In this paper, the fundamental problem of MU-MIMO scalability is tackled through a novel signal-processing approach, which is called degree-2 vector perturbation (D2VP). Unlike the conventional VP approaches that aim at minimizing the transmit-to-receive energy ratio through searching over an N-dimensional Euclidean space, D2VP shares the same target through an iterative-optimization procedure. Each iteration performs vector perturbation over two optimally selected subspaces. By this means, the computational complexity is managed to be in the cubic order of the size of MU-MIMO, and this mainly comes from the inverse of the channel matrix. In terms of the performance, it is shown that D2VP offers comparable bit-error-rate to the sphere encoding approach for the case of small MU-MIMO. For the case of medium and large MU-MIMO when the sphere encoding does not apply due to unimplementable complexity, D2VP outperforms the lattice-reduction VP by around 5-10 dB in Eb/No and 10-50 dB in normalized computational complexity.

Combined channel estimator for pilot-assisted wireless OFDM communication systems

The paper investigates two types of combined channel estimator (CCE) for pilot-assisted orthogonal frequency division multiplexing mobile communication systems. The CCE-type1 is a double maximum-likelihood (ML) based estimator, which works under a limit condition that the number of pilot tones should not be smaller than the channel length. The bit-error-rate performance can be improved significantly by employing this estimator. The CCE-type2 is a second-order polynomial model and ML combined approach. It has better performance than the traditional approach when the limit condition is not satisfied. Simulation results are given to corroborate our discussion.