Yongzhe Xie

Two EM-type channel estimation algorithms for OFDM with transmitter diversity

Combining Orthogonal Frequency Division Multiplexing (OFDM) with transmitter diversity can be used for capacity improvement in high-rate wireless data communication systems. For coherent detection in such systems, channel state information (CSI) is required. In this paper we investigate a Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm to iteratively estimate the channel impulse responses associated with multiple transmitters and the receiver. The performance of the estimator is compared with a previously proposed Expectation-Maximization (EM) based algorithm in terms of convergence rate.

Minimum outage probability transmission with imperfect feedback for MISO fading channels

We study optimal transmission strategies in terms of minimum outage probability for a fading channel with multiple transmit antennas and a single receive antenna. We consider two cases of imperfect channel state information (CSI) feedback: mean feedback and covariance feedback. In both cases, the optimum strategy is shown to be transmission of multiple data streams to the same directions as when maximizing the ergodic channel capacity, but with different power allocation strategies which are closely related to the target rate. In the mean feedback case, the optimal power allocation strategy is also related to the accuracy of the feedback CSI, which affects significantly the achievable outage capacity.

An EM-based channel estimation algorithm for OFDM with transmitter diversity

We study channel estimation for OFDM systems utilizing transmitter diversity and operating over multipath fading channels. An expectation-maximization (EM) based estimation algorithm is introduced and compared to least-squares based estimation algorithms. At each iteration and for every OFDM link, the EM algorithm partitions the problem of estimating a multi-input channel into independent channel estimations for each transmit-receive antenna pair. It is shown that the EM algorithm is more robust to multipath channel delay profile variations and can be implemented more efficiently compared to a previously proposed algorithm.

On Some Near Optimal Low Complexity Detectors for MIMO Fading Channels

We introduce several low complexity sub-optimal MIMO detection schemes based on the List-BLAST algorithm, which exhausts the constellation points in the first layer of a BLAST scheme to generate multiple candidate solutions from which the maximum likelihood solution is determined. The candidates can also be used as initial points for the space alternating generalized expectation-maximization (SAGE) algorithm to further improve performance. The proposed schemes can achieve close to optimal performance for both hard and soft output detection with lower complexity than that of the sphere detection in our simulation settings

Optimal bandwidth allocation for the data and feedback channels in MISO-FDD systems

In frequency-division duplex (FDD) systems, channel-state information (CSI) is estimated by the receiver and then fed back to the transmitter through a feedback link, which inevitably requires additional bandwidth and power. In this letter, we jointly study optimal bandwidth allocation between the data channel, modeled as a flat-fading multiple-input single-output (MISO) channel, and the feedback channel for maximum average throughput in the data channel using a beamforming scheme. We consider two models of the partial CSI at the transmitter (CSIT): the noisy CSIT, modeled as jointly Gaussian with the actual channel state, and the quantized CSIT. In the first model, we use distortion-rate theory to relate the CSIT accuracy to the feedback-link bandwidth. In the second model, we derive a lower bound on the achievable rate of the data channel based on the ensemble of a set of random quantization codebooks. We show that in the MISO flat-fading channel case, beamforming based on feedback CSI can achieve an average rate larger than the capacity without CSIT under a wide range of mobility conditions.

Some results on the sum-rate capacity of MIMO fading broadcast channels

We study the ergodic sum-rate capacity of the fading MIMO broadcast channel which is used to model the downlink of a cellular system with N/sub t/ transmit antennas at the,base and K mobile users each having N/sub r/ receive antennas. Assuming perfect channel state information (CSI) for all users is available at the transmitter and the receivers, we evaluate the sum-rate capacity numerically using the duality between uplink and downlink. Assuming Nt K, we also derive both upper and lower bounds on the sum-rate capacity to study its increase rate due to multi-user diversity. Finally, we compare three transmission schemes which use the single-user-MIMO scheme (SU-MIMO), ranked known interference (RKI) and zero-forcing beamforming (ZFB), respectively, to transmit to a selected set of users in order to approach the sum-rate capacity. We show that both ZFB and RKI outperform SU-MIMO in a cellular downlink scenario. when many mobile users are present.

A novel low complexity detector for MIMO system

We propose a space alternating generalized expectation-maximization (SAGE) aided List-BLAST detection scheme, which can achieve performance close to that of the maximum-likelihood detector with low computational complexity. The SAGE algorithm searches for the ML solution iteratively by resolving the interference among signals from different transmit antennas. To improve the probability of convergence to the ML solution, multiple initial points are used. The List-BLAST algorithm, which exhausts the constellation points in the first layers of a BLAST detection scheme, is shown to be an excellent way to generate initial points. The complexity of the proposed detection scheme is compared with that of the sphere detection scheme and it is shown to have a number of implementation advantages.

Outage probability for MISO fading channels with imperfect feedback

An optimal transmission strategies in terms of minimum outage probability for a fading channel with multiple transmit antennas and a single receive antenna is studied. We consider two cases of imperfect channel state information (CSI) feedback, mean feedback and covariance feedback. In both cases the optimum strategies are shown to be transmission of multiple data streams to the same directions as when maximizing the ergodic channel capacity, but with different power allocation strategies related to the target rate. Moreover, the accuracy of the feedback CSI affects significantly the achievable outage capacity in the case of mean feedback; the outage capacity achieved in the case of covariance feedback is much lower than that in the case of mean feedback. Therefore, accurate tracking of the instantaneous CSI is essential in maximizing outage capacity.

Some results on the linear prediction of bandlimited fading processes

Channel state information at the transmitter (CSIT) is useful in many wireless communication systems, and is usually obtained by feedback in frequency division duplex (FDD) systems. To compensate for the feedback delay, prediction techniques are often used at the transmitter or the receiver side. We study the design and performance analysis of linear prediction of a bandlimited complex Gaussian fading process. We consider prediction based on both noiseless and noisy past samples of the fading process and study both finite and infinite linear minimum mean square error (MMSE) prediction filters. In particular, we derive the MMSE achievable by an infinite length linear filter in the case of prediction based on noisy past samples. We also study the design of robust prediction filters whose coefficients are independent of the second order statistics of the fading process.