Naveen K. D. Venkategowda

WR based semi-blind channel estimation for frequency-selective MIMO MC-CDMA systems

In this paper, we propose a novel whitening-rotation (WR) based semi-blind (SB) scheme for frequency-selective channel estimation in multiple-input multiple-output (MIMO) multi-carrier (MC) CDMA systems. This scheme is based on a low complexity multi-path multi-carrier decorrelator (MMD) receiver structure developed for the MIMO MC-CDMA system. It is shown that the MMD based receiver naturally enables the formulation of the SB scheme by reducing the frequency-selective MIMO MC-CDMA channel to a flat fading channel matrix of appropriate dimension. Thus, it results in a significant reduction in the computational complexity usually associated with frequency-selective MIMO channel estimation. Further, we derive the Cramer-Rao bound (CRB) to characterize the mean squared error (MSE) performance of the proposed SB scheme. For performance comparison of the proposed SB estimator, we also derive the training estimate and the uncertainty based robust estimate of the frequency-selective MIMO MC-CDMA channel. Simulation results demonstrate that the proposed SB scheme achieves a significantly lower MSE of estimation compared to the competing training and robust estimation schemes.

Precoding for Robust Decentralized Estimation in Coherent-MAC-Based Wireless Sensor Networks

This letter proposes novel precoding techniques for robust decentralized parameter estimation with only imperfect channel state information (CSI) in a coherent multiple access channel based wireless sensor network. For scalar parameter estimation, the proposed technique minimizes the worst case estimation error arising due to the channel uncertainties while ensuring the maximum gain at each receive antenna. For vector parameter estimation, since the general noisy measurement case is intractable, a robust precoder is developed for noiseless sensor measurements that eliminates the need for postprocessing at the fusion center while simultaneously minimizing the worst case estimation error. Simulation results show that the proposed techniques have a superior performance in comparison to imperfect CSI agnostic estimation techniques.

Optimal Minimum Variance Distortionless Precoding (MVDP) for Decentralized Estimation in MIMO Wireless Sensor Networks

In this letter, we present a framework for optimal minimum variance distortionless precoder (MVDP) design towards decentralized estimation of a vector parameter in a coherent multiple access channel based multiple-input multiple-output (MIMO) wireless sensor network. The proposed MVDP scheme yields the optimal minimum variance distortionless parameter estimate at the fusion center without the necessity of any receive processing. A closed form expression is derived for the mean square estimation error of the MVDP and it is demonstrated that it asymptotically achieves the centralized minimum mean square error bound. Further, we derive the optimal decentralized estimation schemes with a total network power constraint (MVDP-T) and per-sensor power constraint (MVDP-P). Simulation results demonstrate the performance of the proposed optimal precoding schemes and also support the analytical results derived.

Cooperative multi-cell beamforming for MIMO unicast/ multicast broadband H.264 scalable video networks

In this paper we propose a novel scheme to jointly determine the optimal transmit/receive beamformers together with multi-user power allocation towards transmission rate maximization in a cooperative MIMO cellular wireless network for unicast/multicast scenarios. For the unicast scenario, we propose a successive constrained eigenbeamforming (SCEB) technique to reduce the inter-user interference and enhance the data rates subject to power constraints. This scheme is further extended to a multicast scenario (SCEB-M) to maximize the sum rate of a user group with group constraints on the transmit power. We also derive optimal schemes to efficiently schedule a subset of users/ groups from the active user set. We employ a practical H.264 scalable video quality model to demonstrate the performance of the presented schemes in realistic video streaming broadband wireless networks. Simulation results show that the proposed SCEB schemes achieve a superior data rate and video quality in comparison to conventional resource allocation schemes in cooperative cellular scenarios.

Semi-definite programming (SDP) relaxation based semi-blind channel estimation for frequency-selective MIMO MC-CDMA systems

In this paper, we propose a semi-definite programming (SDP) relaxation based semi-blind (SRSB) channel estimation scheme for frequency-selective multiple-input multiple-output (MIMO) multi-carrier code division for multiple access (MC-CDMA) systems. The SRSB scheme is derived from the multi-path multi-carrier decorrelator (MMD) based robust channel estimation framework developed for MIMO MC-CDMA. We formulate the semi-blind channel estimation scenario for MIMO MC-CDMA systems as a convex quadratic programming (QP) problem. Subsequently with an approximate rank relaxation this is recast as an equivalent SDP problem. Hence, the SDP solvers utilized in maximum likelihood MIMO symbol detection can be utilized to obtain the semi-blind channel estimate, thereby potentially enhancing the estimation performance without the need for additional computational resources. Simulation results demonstrate that the mean-squared error (MSE) performance of the SDP relaxation based semi-blind estimation is significantly superior compared to that of the conventional training based least-squares estimator.

Bandwidth efficient optimal superimposed pilot design for channel estimation in OSTBC based MIMO–OFDM systems

Abstract This paper proposes optimal superimposed pilot (SIP) sequence design and pilot placement towards mean square error (MSE) minimization for channel estimation in spatially correlated/uncorrelated MIMO–OFDM channels. For uncorrelated channels, a closed form expression is derived for the optimal pilot sequence, number of pilot subcarriers and pilot locations. For correlated channels, the problem of designing the optimal SIP sequence is formulated as a semidefinite program. The proposed schemes lead to a substantial increase in the bandwidth efficiency since it employs pilot symbols on a significantly fewer number of subcarriers in comparison to existing schemes. It is shown that the proposed techniques achieve the Cramer–Rao bounds. In addition, a closed form analytical expression is derived for the bit-error rate of orthogonal space–time block codes (OSTBC) based MIMO–OFDM systems including the effect of channel estimation error arising from the proposed SIP based estimation techniques. Simulation results demonstrate the improved estimation performance and bandwidth efficiency of the proposed schemes.

Pilot based channel estimation for frequency selective multi-user MIMO MC-CDMA systems

Multiple-input multiple-output (MIMO) multi-carrier code division multiple access (MC-CDMA) wireless systems are sensitive to multi-user interference (MUI), which increases with increase in the number of users. In order to study its effect, pilot based linear channel estimators are derived considering also the effect of MUI in frequency-selective MIMO MC-CDMA wireless systems. The proposed schemes are based on the novel multi-path multi-carrier decorrelator (MMD) receiver structure and include the maximum likelihood (ML), Wiener filter (WF) and matched filter (MF) techniques. Further, we derive closed form expressions for the biases and variances of the various estimators. Simulation results demonstrate the MSE performance of the proposed estimators. Further, the derived analytical expressions can also be seen to accurately predict the simulation results.

Multi-user beamforming for sum-rate maximization in frequency-selective MIMO MC-CDMA systems

In this paper we propose novel time domain beamforming techniques for nulling multi-user interference in frequency-selective multiple-input multiple-output (MIMO) multi-carrier code division multiple access (MC-CDMA) systems. First a multi-path multi-carrier decorrelator (MMD) receiver is derived, which transforms a frequency selective MIMO MC-CDMA system to an equivalent flat fading multi-user MIMO system of appropriate dimension. Based on the MMD receiver, we propose a joint path and antenna selection based block diagonalization scheme to cancel the multiuser interference. Further, a successive constrained eigenbeamforming (SCEB) algorithm is developed which maximizes the signal to interference-plus-noise ratio (SINR) at each user. The proposed SCEB beamforming technique can support a higher number of users compared to block diagonalization techniques making it ideal to increase the spectral efficiency of the system.

MVDR-Based Multicell Cooperative Beamforming Techniques for Unicast/Multicast MIMO Networks With Perfect/Imperfect CSI

In this paper, we consider unicast/multicast multicell cooperative transmission with interference among users/user groups. In this context, we derive the optimal minimum variance distortionless response (MVDR)-based successive minimum variance beamforming (SMVB) scheme that achieves a superior sum-rate performance compared with the block diagonalization scheme. Subsequently, we derive an optimal joint power allocation and broadcast beamforming scheme for multicell cooperative broadcast transmission for a pooled power constraint at the base stations. This scheme is extended to include per base station power constraints by formulating it as a relaxed semi-definite program (SDP). We also consider the multicell cooperative uplink scenario and derive a successive multiuser (MU) uplink beamforming (SMUB) scheme that maximizes the signal-to-interference-plus-noise ratio (SINR) of each user. Next, we consider imperfect channel state information (CSI) and derive a robust beamforming scheme for the downlink, based on minimizing the worst-case interference by formulating it as a second-order cone program. It is demonstrated that the corresponding robust beamformer for the uplink transmission can be derived by employing the multidimensional covariance fitting approach. Simulation results are presented to demonstrate the superior sum-rate performance of the proposed multicell transmission schemes. The performance is also compared with several bounds for cooperative multicell scenarios.