IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

To meet growing target data rates, future wireless networks will be heterogeneous with macro and pico base stations (BSs). Allocating resources and managing interference between various types of BSs are of primary importance for achieving acceptable throughput in cell edges. In this work, we propose the interference canceling block modulation (ICBM) scheme for interference management in heterogeneous networks. We provide analytical design methods for ICBM and study the application of ICBM in heterogeneous wireless networks. Our results essentially show that ICBM acts as a virtual resource, significantly improving the data rates for cell-edge users as well as the cell average throughput over the conventional techniques in typical interference scenarios arising in heterogeneous networks. © 2012 IEEE.

Department of Electrical Engineering

IEEE Journal on Selected Topics in Signal Processing

Block modulation for interference management in heterogeneous wireless networks

In multicarrier systems, cyclic prefix (CP) is introduced between two symbols to mitigate inter block interference (IBI). The CP length should be equal or more than channel impulse response (CIR) to ensure IBI free system. However, in the interest of spectral efficiency, if the CP is chosen to be less than the (worst case) CIR length, then a time domain channel shortening prefilter (CSP) can be used to truncate or shape the CIR. In [1], we proposed a null-space exploiting CSP (NE-CSP) which is has a lower complexity when compared to the linear minimum mean square error (LMMSE) [2]. In this paper, we propose a symbol-by-symbol adaptive null-space exploiting CSP (SANE-CSP) scheme based on the NE-CSP structure, which is computationally inexpensive. The order of complexity of SANE-CSP is O(n c 2), whereas the computational complexity order for NE-CSP [1] is O(n c 3) and that of the decoding-delay optimised LMMSE [2] is close to for O(n c 4). The SANE-CSP for n c = 100, has a block error rate performance 3 dB poorer than the decoding-delay optimised LMMSE, but with only 0.01% computational complexity. © 2011 National Institute of Inform.

2011 the 14th International Symposium on Wireless Personal Multimedia Communications: Communications, Networking and Applications for the Internet of Things, WPMC'11

Symbol-by-symbol adaptive null-space exploiting (SANE) channel truncation for fading OFDM channels

Different-complexity Multi-Cell Processing (MCP) schemes employing Distributed Signal-to-Interference-Leakage-plus-Noise-Ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison to the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the achievable cell-edge throughput and offering different geographic rate profile distributions as well as meeting different delay requirements. © 2011 IEEE.

Fulltext

2011 IEEE Wireless Communications and Networking Conference, WCNC 2011

Distributed downlink Multi-Cell Processing requiring reduced-rate back-haul data exchange

In OFDM system, with fixed cyclic prefix (CP) length, inter block interference (IBI) and inter carrier interference will be present if the channel impulse response (CIR) is larger than the CP length. This problem can be mitigated by design a time domain filter at the receiver, which can shorten or shape the effective CIR to become less than the CP length. This paper proposes a novel method to design a channel shortening prefilter (CSP) for MIMO-OFDM systems, by defining a measurement model which has an underdetermined set of equations. This model is always applicable when the number of transmit antennas (actually transmit streams) is less than the number of receive antennas. The proposed Null-space Exploiting CSP (NE-CSP) removes the IBI and ICI nearly completely, but in the simplest form, has a loss in diversity. It is possible to reclaim this diversity by using the multiple layers (or filters) within the NE-CSP structure. Simulation results indicate that, compared to existing channel truncation methods, the NE-CSP is not only computationally attractive, but can also gives a gain of 3dB to 5dB in bit error rate performance (BER) performance at high SNRs. ©2010 IEEE.

Proceedings of 16th National Conference on Communications, NCC 2010

Null-space exploiting channel shortening prefilter (NE-CSP) for MIMO-OFDM

Tensor-based spatial smoothing (TB-SS) is a preprocessing technique for subspace-based parameter estimation of damped and undamped harmonics. In TB-SS, multichannel data is packed into a measurement tensor. We propose a tensor-based signal subspace estimation scheme that exploits the multidimensional invariance property exhibited by the highly structured measurement tensor. In the presence of noise, a tensor-based subspace estimate obtained via TB-SS is a better estimate of the desired signal subspace than the subspace estimate obtained by, for example, the singular value decomposition of a spatially smoothed matrix or a multilinear algebra approach reported in the literature. Thus, TB-SS in conjunction with subspace-based parameter estimation schemes performs significantly better than subspace-based parameter estimation algorithms applied to the existing matrix-based subspace estimate. Another advantage of TB-SS over the conventional SS is that TB-SS is insensitive to changes in the number of samples per subarray provided that the number of subarrays is greater than the number of harmonics. In this paper, we present, as an example, TB-SS in conjunction with ESPRIT-type algorithms for the parameter estimation of one-dimensional (1-D) damped and undamped harmonics. A closed form expression of the stochastic Cramr-Rao bound (CRB) for the 1-D damped harmonic retrieval problem is also derived. © 2006 IEEE.

IEEE Transactions on Signal Processing

Tensor-based spatial smoothing (TB-SS) using multiple snapshots

Robust signal processing methods deal with design of estimators that exhibit resilience to uncertainties in the user specified inputs regarding the operating conditions. The H∞ estimator was proposed as a possible replacement to the Kalman filter while operating in the presence of uncertainties in the statistical and parametric inputs to the filter. The results in this paper compare the Mean Squared Error (MSE) performance (or MSE robustness) of the H∞ estimator and the Kalman filter under conditions of misspecified statistics. This study would facilitate the user to choose the better estimator under the given operating conditions. The results presented here show that under different operating conditions both the filters conditionally dominate one over the other. ©2010 IEEE.

Mean square robustness of linear game theoretic estimators

OFDMA (Orthogonal frequency division multiple access) based systems have been considered as a candidate for future wireless communication systems. In such a system, it is important to provide high data rate services for users with high mobility. For this purpose, decision-directed channel tracking (DDCT) techniques have been investigated for OFDM systems in high mobility environments. The performance of the DDCT in OFDMA systems depends on the assigned channel condition, and therefore it is important to allocate a proper channel to each user. The purpose of this paper is to propose an adaptive channel assignment method which enhances the DDCT improvement in an OFDMA system, where the former numbered resource blocks (RBs) in OFDMA frame are preferentially allocated to the users moving at a high speed. Computer simulation results show that the proposed method is effective in improving throughput performance of OFDMA systems in a high Doppler frequency condition. ©2010 IEEE.

4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings

Adaptive channel assignment and pilot-less channel tracking method for OFDMA systems

The need for covert communication in tactical battlefields has developed the ideas of low probability of intercept (LPI) networks. Spread spectrum communication is used for LPI communication. Multicarrier CDMA is a new type of spread spectrum technique that has been developed in recent years. Most of the works in MC-CDMA are focused on finding out BER performance of it when different users share the same time and spectral ranges. But, LPI performance of MC-CDMA is not explored much. In this paper we have focused on understanding the LPI property of MC-CDMA. We have found out that increasing spreading factor and application of forward error control coding improve LPI property of MC-CDMA based wireless networks to a great extent. ©2010 IEEE.

A multicarrier CDMA based low probability of intercept network

Interference alignment, as proposed in [1], is a joint multi-base-station precoding technique where each interfering base-station determines its precoder so as to obtain aligned interfering signals at each user. Determination of such precoders requires complete channel state information of all the interfering links to be present at all the base-stations. In this paper, we present a modified form of interference alignment based on locally-available channel state information at the user equipment. We consider the downlink of a wireless system where basestations and user equipments are equiped with two antennas each and scheduling of users is done based on Fractional Frequency Reuse. Assuming an MMSE receiver at the user equipment, an expression for the optimal precoder to be used by the interfering base-stations is derived so that there is zero interference after MMSE equalization. We also give an example for the case where there is uncancelled interference despite the use of these precoders. The effect of this uncancelled interference is overcome by the use of a robust LLR developed in [2]. Simulation results that demonstrate the performance of the proposed technique are presented. ©2010 IEEE.

Robust LLR aided low feedback precoding for interference alignment

We consider the decoding of LDPC codes in presence of non-Gaussian noise, especially a set of E-mixture models. For each of these models, the optimal LLRs are presented. We study the performance degradation due to the use of incorrectLLR in presence of a given noise model. Without modifying the existing LDPC decoder, we propose robust initial LLR which require minimum knowledge about the underlying noise modeland are computationally less complex. Since BER simulations are computationally heavy, we use density evolution to compare the thresholds of different LLRs.

IEEE International Symposium on Information Theory - Proceedings

Robust initial llrs for iterative decoders in presence of non-gaussian noise

This paper proposes a joint channel-estimation method for the desired and interfering channels for cell edge users in reuse-1 orthogonal frequency-division multiplexing (OFDM) cellular systems. The following assumptions are made in proposing the algorithm: 1) The desired and interferer's channel multipath delays do not overlap; 2) the same pilot sequence is sent from the desired and interfering base stations (BSs); and 3) reuse-3 preamble symbols, as in the preamble structure in IEEE 802.16d/e (Wimax) systems, are used to obtain initial channel estimates without interference. If we make these assumptions, then it is possible to estimate the desired and interfering channels, even with reuse-1 pilots. The proposed pilot-based channel estimation technique exploits the delay subspace structure to reduce the impact of cochannel interference (CCI) on channel estimation. Delay subspace refers to the set of basis vectors spanning the frequency response of the desired and interfering multipath channels. This enables us to jointly estimate and track the desired and interfering channels with a lower mean-squared error (MSE), when compared with the conventional modified least-squares (mLS) technique, which ignores the structure of interference. The significance of accurate channel estimates in symbol detection schemes is demonstrated for systems employing two or more receiver antennas. The proposed channel estimator significantly improves the performance of symbol-detection schemes based on either interference nulling combiner (INC) or minimum MSE diversity combiner (MMSE-DC), when compared with detection schemes using mLS-based channel estimates. Analytical expressions are derived for the MSE of the estimated multipath delays. Simulation results are also provided to show the improved performance for the proposed channel-estimation method compared with the mLS-based channel estimation method, when used in conjunction with INC and MMSE-DC detectors. © 2009 IEEE.

IEEE Transactions on Vehicular Technology

Interference rejection for parametric channel estimation in reuse-1 cellular OFDM systems

Spatial smoothing is a widely used preprocessing scheme for direction-of-arrival (DOA) estimation of more than one source from a single snapshot, although the effective array aperture gets reduced by this process. In this paper we propose a preprocessing scheme applicable for DOA estimation algorithms that exploit the shift invariance property of the array steering matrix and call it spatial smoothing with improved aperture (SSIA). SSIA, when applied to a noise corrupted data vector, improves the effective array aperture significantly as opposed to conventional spatial smoothing. Simulations confirm the significant performance gain provided by SSIA in conjunction with Unitary ESPRIT. © 2009 IEEE.

IEEE Signal Processing Letters

Single snapshot spatial smoothing with improved effective array aperture

We propose a novel subspace-based 2-D damped harmonic retrieval algorithm that uses a single snapshot of data. The data is packed into a measurement tensor and spatial smoothing is applied to it to get a spatially smoothed tensor. We observe a structure inherent in the spatially smoothed tensor. This structure can be fully exploited by constructing multiple higher-order tensors from the spatially smoothed tensor and by running parameter estimation algorithm multiple times, one for each dimension. In this paper we propose to construct a single higher-order tensor and perform a single higher-order singular value decomposition (HOSVD) for estimating the normalized frequencies along the two dimensions. The proposed algorithm performs significantly better than Tensor-ESPRIT applied to the spatially smoothed tensor, and matrix-based approaches. Moreover, it is insensitive to changes in the number of samples per subarray. Our work can be extended to R-D damped harmonic retrieval problems. ©2009 IEEE.

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

2-D normalized frequency estimation using 4-way tensor processing

Single Snapshot R-D Unitary Tensor-ESPRIT Using an Augmentation of the Tensor Order (SS-U-TE-ATO) is a subspace-based parameter estimation technique for R-dimensional (R-D) undamped harmonics using a single snapshot of data. In SS-U-TE-ATO the measurement data is packed into a measurement tensor to which spatial smoothing is applied. We propose the construction of R higher-order tensors from the spatially smoothed tensor by exploiting the inherent structure of the spatially smoothed tensor. In the next step of SS-U-TEATO, R enhanced real-valued signal subspace estimates, one for each dimension, are obtained from the R complex-valued higher-order tensors. We show that SS-U-TE-ATO performs significantly better than Unitary Tensor-ESPRIT (U-TE) directly applied to the spatially smoothed tensor. Moreover, for each dimension, SS-U-TE-ATO is almost insensitive to changes in the number of sensors per subarray provided that the number of subarrays is greater than the number of sources. Thereby we avoid the problem of selecting the optimum subarray size for a given source configuration. © 2009 IEEE.

CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing

Single snapshot R-D unitary tensor-ESPRIT using an augmentation of the tensor order

Performance of spatial multiplexing multiple-input multiple-output (MIMO) wireless systems can be improved with channel state information (CSI) at both ends of the link. This paper proposes a new linear diagonal MIMO transceiver, referred to as co-ordinate interleaved spatial multiplexing (CISM). With CSI at transmitter and receiver, CISM diagonalizes the MIMO channel and interleaves the co-ordinates of the input symbols (from rotated QAM constellations) transmitted over different eigenmodes. The analytical and simulation results show that with co-ordinate interleaving across two eigenmodes, the diversity gain of the data stream transmitted over the weaker eigenmode becomes equal to that of the data transmitted on the stronger eigenmode, resulting in a significant improvement in the overall diversity. The diversity-multiplexing tradeoff (DMT) is analyzed for CISM and is shown that it achieves higher diversity gain at all positive multiplexing gains compared to existing diagonal transceivers. Over rank n MIMO channels, with input symbols from rotated n-dimensional constellations, the DMT of CISM is a straight line connecting the endpoints (0,NtNr) and (min{Nt,Nr}, 0), where Nt, and Nr} are the number of transmit and receive antennas, respectively. © 2006 IEEE.

IEEE Transactions on Wireless Communications

Co-ordinate interleaved spatial multiplexing with channel state information

Cooperative relay communications can significantly improve the reliability of data transmission over wireless fading channels by implementing spatial diversity in a distributed fashion. Orthogonal decode and forward (ODF) relaying achieves maximum diversity provided by the source-destination and relaydestination channels, but suffers from low spectral efficiency. We propose a novel ODF protocol having higher spectral efficiency without sacrificing the diversity gain. We analyze the symbol error probability of the proposed protocol and also present simulation results. © 2009 IEEE.

IEEE Communications Letters

Orthogonal decode and forward relaying with improved spectral efficiency

In the emerging broadband wireless networks such as IEEE 802.16m and LTE-A networks which employ universal frequency reuse-1, the cell coverage is predominantly limited by the co-channel interference. Bit level data repetition, and conventional multi-antenna maximal-ratio-combining (MRC) techniques are typically used to improve the signal-to-interference-plusnoise ratio (SINR) at the receiver. Simple data repetition does not guarantee efficient interference suppression and it reduces spectrum efficiency. In this paper, we propose a symbol level data repetition technique called conjugate data repetition (CDR), which transmits the modulation alphabet of the desired signal and its complex-conjugate in distinct sub carriers. The CDR operation is performed across all base stations in a synchronous manner. We show that minimum mean-square error (MMSE) filtering of the complex-valued signal and its conjugated copy, provides a high interference cancellation (IC) gain. For repetition factor greater than 2, we propose a combination of conjugate repetition and random phase rotation of the repeated symbols. Simulation results show that CDR with a repetition factor 2 or 3 can provide a significant advantage in coverage/reliability for cell edge users. ©2009 IEEE.

GENERAL

IEEE International Conference on Communications

Interference mitigation using conjugate data repetition

Pilot assisted channel tracking (PACT) has been very popular for channel estimation in OFDM systems. However, as the mobility in the system increases and one has to maintain a high accuracy in channel estimation, the pilot overhead typically has to be increased. Emerging cellular OFDM standards are expected to use about 6-12% pilot overhead per stream, and any possible reduction in pilot overhead would be useful. Decision directed channel tracking (DDCT) can help reduce pilot overhead, but is known to suffer from error propagation at high fade rates. In emerging broadband wireless systems promising peak bit rates of 50 Mbps or more, saving on pilot overhead by using DDCT schemes would be highly attractive provided: (a) Such a DDCT approach does not suffer from error propagation and has an error rate performance comparable to (or better than) PACT schemes even at high fade rates; (b) The computational complexity of such a DDCT approach is not significantly more than that of the MMSE based PACT scheme. In this work, we propose a low complexity DDCT method which exploits the structure of the regression matrix in conjunction with robust statistics to mitigate the effect of error propagation. It has a much lower computational complexity and a better error rate performance than the decision directed EM-Kalman and other existing robust statistics based DDCT schemes. The proposed method also outperforms a 12.5% pilot overhead based PACT scheme with only a modest increase in computational complexity. ©2009 IEEE.

Low complexity decision directed channel tracking for high mobility OFDM systems

Channel estimation for Alamouti space frequency coded (ASFC) 2 × 2 and 2 × 1 MIMO OFDM systems, employing Decision Directed Channel tracking (DDCT) for high fade rates and long frame durations is studied here. Errors in the regression matrix (i.e. equalisation errors) have a Gaussian distribution, but due to error propagation problem of DDCT at high fade rates and long symbol durations, large deviations from the Gaussian model is observed. Hence the problem of channel estimation can be formulated as an outlier contaminated Gaussian linear regression problem. Most of the classical estimators like Least squares (LS) and Expectation Maximisation (EM) algorithm perform poorly in presence of outliers. Moreover, for a MIMO system the source of outliers are the erroneous decisions of any of the multiple input channels. Here, we propose to use the EM algorithm to partition multiple input channel into independent estimations for each transmit-receive antenna pair and provide an iterative framework for solving the multiple regression problem. EM algorithm is made robust using the Huber's M principle (for the E and the M steps) and it is shown analytically that mean square error (MSE) performance improves as compared to existing schemes which assume Gaussian noise. The simulated symbol error rate (SER) and MSE performances demonstrate the significant gains of the proposed robust EM algorithm over existing DDCT techniques at high normalised fade rates for the given system. © 2008 IEEE.

GLOBECOM - IEEE Global Telecommunications Conference

Robust channel tracking in fast fading MIMO channels

A robust cost function for log likelihood ratio (LLR) computation is proposed for turbo coded OFDM systems in the presence of narrowband interference (NBI) and co-channel interference (CCI). In systems employing standards such as the IEEE 802.16d/e, CCI behaves like NBI with the number of affected subcarriers ranging from 10% to 30%. The combined effect of NBI and thermal Gaussian noise leads to a contaminated Gaussian (CG) noise probability density function (pdf). Simulation results indicate that the proposed method performs very close to the optimal method where the optimal method computes the LLR using the CG pdf. While the optimal method requires knowledge of the NBI power, the fraction of subcarriers contaminated by NBI and the NBI pdf, the proposed method does not require knowledge of these parameters. © 2008 IEEE.