Aditya K. Jagannatham

Whitening-rotation-based semi-blind MIMO channel estimation

This paper proposes a whitening-rotation (WR)-based algorithm for semi-blind estimation of a complex flat-fading multi-input multi-output (MIMO) channel matrix H. The proposed algorithm is based on decomposition of H as the matrix product H=WQ/sup H/, where W is a whitening matrix and Q is unitary rotation matrix. The whitening matrix W can be estimated blind using only received data while Q is estimated exclusively from pilot symbols. Employing the results for the complex-constrained Cramer-Rao Bound (CC-CRB), it is shown that the lower bound on the mean-square error (MSE) in the estimate of H is directly proportional to its number of unconstrained parameters. Utilizing the bounds, the semi-blind scheme is shown to be very efficient when the number of receive antennas is greater than or equal to the number of transmit antennas. Closed-form expressions for the CRB of the semi-blind technique are presented. Algorithms for channel estimation based on the decomposition are also developed and analyzed. In particular, the properties of the constrained maximum-likelihood (ML) estimator of Q for an orthogonal pilot sequence is examined, and the constrained estimator for a general pilot sequence is derived. In addition, a Gaussian likelihood function is considered for the joint optimization of W and Q, and its performance is studied. Simulation results are presented to support the algorithms and analysis, and they demonstrate improved performance compared to exclusively training-based estimation.

Cramer-Rao lower bound for constrained complex parameters

An expression for the Cramer-Rao lower bound (CRB) on the covariance of unbiased estimators of a constrained complex parameter vector is derived. The application and usefulness of the result is demonstrated through its use in the context of a semiblind channel estimation problem.

Training-based and semiblind channel estimation for MIMO systems with maximum ratio transmission

This paper is a comparative study of training-based and semiblind multiple-input multiple-output (MIMO) flat-fading channel estimation schemes when the transmitter employs maximum ratio transmission (MRT). We present two competing schemes for estimating the transmit and receive beamforming vectors of the channel matrix: a training-based conventional least-squares estimation (CLSE) scheme and a closed-form semiblind (CFSB) scheme that employs training followed by information-bearing spectrally white data symbols. Employing matrix perturbation theory, we develop expressions for the mean-square error (MSE) in the beamforming vector, the average received signal-to-noise ratio (SNR) and the symbol error rate (SER) performance of both the semiblind and the conventional schemes. Finally, we describe a weighted linear combiner of the CFSB and CLSE estimates for additional improvement in performance. The analytical results are verified through Monte Carlo simulations

MIMO indoor WLAN channel measurements and parameter modeling at 5.25 GHz

We present measurement results of indoor multiple-input multiple-output (MIMO) multipath wireless channels in the unlicensed national information infrastructure (U-NII) 5.25 GHz band for wireless local area network (WLAN) applications. MIMO channel impulse responses were measured at different locations using co-polarized (copol) and cross-polarized (crosspol) antennas under line-of-sight (LOS) and non-line-of-sight (NLOS) channel conditions in office and cafeteria type environments. Ricean k-factors, correlations, crosspol discriminations (XPD), pathloss (PL) and RMS delay spread (/spl tau//sub rms/) were computed for different antenna configurations (copol/crosspol) and different channel conditions (LOS/NLOS). Models were developed to characterize the distance dependent variation and the statistical deviations of these parameters.

Selective DF Protocol for MIMO STBC Based Single/Multiple Relay Cooperative Communication: End-to-End Performance and Optimal Power Allocation

In this paper, we consider the performance of a selective decode-and-forward (DF) relaying based multiple-input multiple-output (MIMO) space-time block coded (STBC) cooperative communication system with single and multiple relays. We begin with a single relay based MIMO STBC system and derive the closed form expression for the end-to-end PEP of coded block detection at the destination node. It is also demonstrated that the MIMO STBC cooperative communication system achieves the full diversity order of the system. We also derive the optimal source relay power allocation, which minimizes the end-to-end decoding error of the cooperative system for a given power budget. Subsequently, for the multiple relay scenario, we consider two different relaying protocols based on two-phase and multi-phase communication. For each of these multi-relay protocols, we derive the closed form expressions for the end-to-end error rate, diversity order, and optimal power allocation. Simulation results are presented to validate the performance of the proposed single and multiple relay based cooperative communication schemes and the derived analytical results. Further, these schemes can also be seen to lead to a performance improvement compared to several other relaying schemes in existing literature.

Game theory based dynamic bit-rate adaptation for H.264 scalable video transmission in 4G wireless systems

In this paper, we propose a game theoretic framework for decentralized H.264 scalable video bit-rate adaptation in 4G wireless networks. The framework presented employs a pricing based utility function towards video streaming quality optimization. An algorithm is presented for iterative strategy update of the competing scalable coded video streaming end users towards an equilibrium allocation. In this context we demonstrate the existence of a Nash equilibrium for the proposed video bit-rate adaptation game based on the quasi-concavity of the net video utility function. Existence of Nash equilibrium ensures efficient usage of the 3G/4G bandwidth resources towards video quality and revenue maximization. We present simulation results to comprehensively illustrate the performance of the above game theoretic video quality adaptation scheme. We also discuss the behavior of the parameters of the net video utility function, their impact on video bit-rate allocation and overall bandwidth utilization of the wireless network.

A semi-blind MIMO channel estimation scheme for MRT

We investigate semi-blind channel estimation for multiple input multiple output (MIMO) quasi-static flat fading channels when maximum ratio transmission (MRT) is employed. We propose a closed-form semi-blind solution (CFSB) for estimating the optimum transmit and receive beamforming vectors of the channel matrix. Employing matrix perturbation theory, we develop expressions for the mean squared error (MSE) in the beamforming vector and average received SNR of both the semi-blind and the conventional least squares estimation (CLSE) schemes. It is found that the proposed estimation technique outperforms CLSE for a wide range of training lengths and training SNRs.

Constrained ML algorithms for semi-blind MIMO channel estimation

We propose and study algorithms for constrained maximum-likelihood (ML) estimation of a unitary matrix in the context of semi-blind multi-input multi-output (MIMO) channel estimation. The flat-fading r/spl times/t MIMO channel matrix, H, for r/spl ges/t can be decomposed as the matrix product H = WQ/sup H/, where W is a whitening matrix and Q is a unitary rotation matrix. Exclusive estimation of Q from pilot symbols has been shown potentially to achieve a 3 dB or greater improvement in terms of channel estimation accuracy. We develop and present the OPML, IGML and ROML algorithms for the constrained estimation of the unitary matrix Q; they are appropriate for a variety of scenarios, e.g., orthogonal pilots, low complexity, etc. Simulation results are provided to demonstrate the efficacy of the algorithms.

Cramer–Rao bound based mean‐squared error and throughput analysis of superimposed pilots for semi‐blind multiple‐input multiple‐output wireless channel estimation

SUMMARY This work presents a study of the mean-squared error (MSE) and throughput performance of superimposed pilots (SP) for the estimation of a multiple-input multiple-output (MIMO) wireless channel. The Cramer–Rao bound (CRB) is derived for SP based estimation of the MIMO channel matrix. Employing the CRB analysis, it is proved that the asymptotic MSE bound is potentially 3 dB lower than the MSE performance of the existing SP mean based estimation (SPME) schemes. Motivated by this observation, a novel SP semi-blind scheme is presented for MIMO channel estimation. This scheme asymptotically achieves the CRB and hence has a lower MSE of estimation when compared with SPME schemes. We also derive closed form expressions for the optimal source-pilot power allocation in SP by maximizing the post-processing signal-to-noise power ratio at the receiver. In the final part, a new result is presented for the worst-case capacity of a communication channel with correlated information symbols and noise. This framework is employed to quantify the throughput performance of SP and also to demonstrate the bandwidth efficiency of SP compared with that of a conventional pilot based system. Copyright

Optimal subcarrier allocation for H.264 based scalable video transmission in 4G OFDMA systems

In this paper, we present a novel scheme for optimal OFDMA subcarrier allocation towards video quality maximization employing the paradigm of H.264 based scalable video coding (SVC). We deduce the rate and quality model parameters for video characterization of the SVC extension of the H.264/AVC and propose an optimization framework for sum quality maximization of the transmitted video streams in unicast and multicast 4G scenarios. We derive the closed form solution for optimal quantizer selection towards net video quality maximization subject to rate constraints of the unicast/ multicast users, taking into account the different modulation and coding rates of the multicast groups in the 4G wireless system. This in turn yields the optimal OFDMA time/frequency resource allocation for video multiplexing. In the simulation results section, we specialize our proposed algorithm in the context of WiMAX based 4G video transmission and demonstrate that our algorithm provides significant improvement in video quality over the content agnostic non-scalable equal symbol rate allocation scheme for unicast and multicast scenarios.