
Suraj SrivastavaIndian Institute of Technology Jodhpur | IITJ · Electrical Engineering Programme
Suraj Srivastava
Doctor of Philosophy
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73
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Publications
Publications (73)
Cooperative hybrid transmit precoder (TP) and receive combiner (RC) design algorithms are conceived for cell-free millimeter wave (mmWave) multiple-input multiple-output (MIMO) networks, operating in the face of asynchronous interference (ASI). To begin with, a Wiener filtering-based optimal hybrid TP/RC (WHB-U) design is proposed for unicast scena...
In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary use...
This paper conceives a hybrid beamforming design (HBF) that maximizes the energy efficiency (EE) of an integrated sensing and communication (ISAC)-enabled millimeter wave (mmWave) multiple-input multiple-output (MIMO) system. In the system under consideration, an ISAC base station (BS) with the hybrid MIMO architecture communicates with multiple us...
Pareto optimal solutions are conceived for radar beamforming error (RBE) and sum rate maximization in short-packet (SP) millimeter-wave (mmWave) integrated sensing and communication (ISAC). Our ultimate goal is to realize ultra-reliable low-latency communication (uRLLC) and real-time sensing capabilities for 6G applications. The ISAC base station (...
Bayesian learning aided massive antenna array based THz MIMO systems are designed for
spatial-wideband
and
frequency-wideband
scenarios, collectively termed as the
dual-wideband
channels. Essentially, numerous antenna modules of the THz system result in a significant delay in the transmission/ reception of signals in the time-domain across th...
A new affine-precoded superimposed pilot (AP-SIP) scheme is conceived for both wireless
channel and radar target parameter estimation in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems. The AP-SIP scheme leads to enhanced est...
Asynchronous distributed hybrid beamformers (ADBF) are conceived for minimizing the total transmit power subject to signal-to-interference-plus-noise ratio (SINR) constraints at the users. Our design requires only limited information exchange between the base stations (BSs) of the mmWave multi-cell coordinated (MCC) networks considered. To begin wi...
In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary use...
This paper proposes an integrated sensing and communication (ISAC) framework based on the orthogonal time-frequency space (OTFS) modulation scheme for millimeter wave (mmWave) multiple-input multiple-output (MIMO) dual functional radar and communication (DFRC) systems. Initially, we derive the delay-Doppler (DD)-domain end-to-end input-output model...
Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequence multiplexing (OTSM)-based systems relying on low-resolution analog-to-digital convertors (ADCs). First, the CSI estimation model is...
Pareto optimal solutions are conceived for radar beamforming error (RBE) and sum rate maximization in short-packet (SP) millimeter-wave (mmWave) integrated sensing and communication (ISAC). Our ultimate goal is to realize ultra-reliable low-latency communication (uRLLC) and real-time sensing capabilities for 6G applications. The ISAC base station (...
In this work, we conceive novel robust hybrid beamformer design schemes for millimeter-wave (mmWave) multi-cell multi-user (MCMU) systems in the presence of channel state information (CSI) uncertainty, that relies on base station (BS) coordination and minimization of total transmit power while ensuring compliance to practical signal-to-interference...
Hybrid transceivers are designed for linear decentralized estimation (LDE) in a mmWave multiple-input multiple-output (MIMO) IoT network (IoTNe). For a noiseless fusion center (FC), it is demonstrated that the MSE performance is determined by the number of RF chains used at each IoT node (IoTNo). Next, the minimum-MSE RF transmit precoders (TPCs) a...
In this work, frequency selective hybrid precoders and combiners are designed for a millimeter wave (mmWave) multiuser (MU) multiple-input-multiple-output (MIMO) downlink underlay cognitive radio network (CRN) utilizing multiple radio frequency (RF) chains and uniform rectangular planar arrays (URPAs) both at the CR base station (CBS) and the secon...
The energy efficiency (EE) of the reconfigurable intelligent surface (RIS) aided multiuser (MU) millimeter wave (mmWave) multi-input multi-output (MIMO) downlink is maximized by jointly optimizing the transmit power and number of active radio frequency (RF) chains. The base band (BB) transmit precoder (TPC) of this system is derived first by using...
An orthogonal affine-precoded superimposed pilot (AP-SIP)-based architecture is developed for the cyclic prefix (CP)-aided single input single output (SISO) and multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) systems relying on arbitrary transmitter-receiver (Tx-Rx) pulse shaping. The data and pilot symbol matrices are...
This work conceives a sparse channel estimation (CE) scheme for multiuser (MU) intelligent reflecting surface (IRS)-aided Terahertz (THz) systems. The proposed framework also incorporates hardware impairments that arise due to manufacturing errors in practical THz systems, such as mutual coupling, irregular antenna spacing, and antenna gain/phase e...
This paper considers a joint radar and communication (JRC) system towards radar cross-section (RCS) parameter and channel estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The proposed algorithms are based on the hybrid mmWave MIMO architecture. First, the orthogo...
Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre-and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimatio...
An orthogonal affine-precoded superimposed pilot-based architecture is developed for the cyclic prefix (CP)-aided SISO and MIMO orthogonal time frequency space systems relying on arbitrary transmitter-receiver pulse shaping. The data and pilot symbol matrices are affine-precoded and superimposed in the delay Doppler-domain followed by the developme...
Hybrid transceivers are designed for linear decentralized estimation (LDE) in a mmWave multiple-input multiple-output (MIMO) IoT network (IoTNe). For a noiseless fusion center (FC), it is demonstrated that the MSE performance is determined by the number of RF chains used at each IoT node (IoTNo). Next, the minimum-MSE RF transmit precoders (TPCs) a...
Hybrid precoders and combiners are designed for cooperative cell-free multi-user millimeter wave (mmWave) multiple-input multiple-output (MIMO) cellular networks for low complexity interference mitigation. Initially, we derive an optimal hybrid transmit beamformer (HTBF) for a broadcast scenario considering both total and per access point (AP) powe...
Robust linear decentralized tracking of a time varying sparse parameter is studied in a multiple-input multiple-output (MIMO) wireless sensor network (WSN) under channel state information (CSI) uncertainty. Initially, assuming perfect CSI availability, a novel sparse Bayesian learning-based Kalman filtering (SBL-KF) framework is developed in order...
A hybrid transceiver architecture is conceived for a cognitive radio (CR) aided millimeter wave (mmWave) multiuser (MU) multiple-input multiple-output (MIMO) downlink system relying on multiple radio frequency (RF) chains both at the CR base station (CBS) and the secondary users (SUs). To begin with, a hybrid transceiver design algorithm is propose...
Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre-and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimatio...
The downlink of a reconfigurable intelligent surface (RIS)-aided multi-user (MU) millimeter wave (mmWave) multiple-input multiple-output (MIMO) system relying on a non-diagonal RIS (NDRIS) phase shift matrix is considered. A max-min fairness (MMF) problem is formulated under the total transmit power constraint while employing joint active hybrid be...
The downlink (DL) of a reconfigurable intelligent surface (RIS)-aided multi-user (MU) millimeter wave (mmWave) multiple-input multiple-output (MIMO) system relying on a non-diagonal RIS (NDRIS) phase shift matrix is considered. A max-min fairness (MMF) problem is formulated under the total transmit power constraint while employing joint active hybr...
Low-complexity fusion rules relying on hybrid combining are proposed for decision fusion in frequency selective millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) sensor networks (SNs). Both centralized (C-MIMO) and distributed (D-MIMO) antenna architectures are considered, where the error-prone local sensor decisions are transm...
Online Bayesian learning-assisted channel state information (CSI) estimation schemes are conceived for single input single output (SISO) and multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) modulated systems. To begin with, an end-to-end system model is derived in the delay-Doppler (DD)-domain, followed by an online CSI...
Linear hybrid beamformer designs are conceived for the decentralized estimation of a vector parameter in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) Internet of Things network (IoTNe). The proposed designs incorporate both total IoTNe and individual IoTNo power constraints, while also eliminating the need for a baseband receive...
Linear hybrid beamformer designs are conceived for the decentralized estimation of a vector parameter in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) Internet of Things network (IoTNe). The proposed designs incorporate both total IoTNe and individual IoTNo power constraints, while also eliminating the need for a baseband receive...
Hybrid precoders and combiners are designed for cooperative cell-free multi-user millimeter wave (mmWave) multiple-input multiple-output (MIMO) cellular networks for low complexity interference mitigation. Initially, we derive an optimal hybrid transmit beamformer (HTBF) for a broadcast scenario considering both total and per access point (AP) powe...
Novel hybrid beamformer designs are conceived for a multi-user multi-cell (MUMC) mmWave system relying on base station (BS) coordination and total transmit power minimization subject to realistic signal-to-interference-plus-noise ratio (SINR) constraints at each mobile station (MS). Initially, a semidefinite relaxation (SDR)-based approach is devel...
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems relying on sparse channel state information (CSI) estimation techniques is conceived. To begin with, a practical MIMO channel model is developed for the THz band that incorporates its molecular absorption and reflection losses, as well as its non-line-of-sig...
A convenient delay, Doppler and angular-(DDA) domain representation of the multiple-input multiple-output (MIMO) wireless channel is conceived for deriving the end to end relationship in the delay-Doppler (DD)-domain for orthogonal time frequency space (OTFS)-based communications. Subsequently, a time-domain pilot based model is developed for estim...
Orthogonal time frequency space (OTFS) waveform based millimeter wave (mmWave) MIMO systems are capable of achieving high data rates in high-mobility scenarios. Hence, transceivers are designed for both analog beamforming (AB) and hybrid beamforming (HB), where we commence by deriving the delay-Doppler (DD)-domain input-output relationship consider...
A hybrid transceiver architecture along with the optimal power allocation is conceived for a downlink millimeter wave (mmWave) multi-input multi-output (MIMO) cognitive radio (CR) system operating in the underlay mode. Towards this, the non-convex objective and constraints of the sum spectral ef-ficiency (SE) maximization problem are simplified by...
Sparse Bayesian learning (SBL)-based channel state information (CSI) estimation schemes are developed for filter bank multicarrier (FBMC) systems using offset quadrature amplitude modulation (OQAM). Initially, an SBL-based channel estimation scheme is designed for a frequency-selective quasistatic single-input single-output (SISO)-FBMC system, rely...
This paper presents low-complexity decision rules as well as the pertinent analysis for data fusion in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). The proposed framework considers both unknown and known parameter scenarios, and the spatial correlation arising due to close proximity of the...
This work conceives dictionary-learning (DL)-based sparse channel estimation schemes for multi-user Terahertz (THz) hybrid MIMO systems incorporating also non-idealities such as hardware impairments and beam-squint effect. Due to the presence of large antenna arrays coupled with frequency selectivity, beam squint effect is significant in THz system...
This work conceives novel target detection and parameter estimation schemes in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) radar (mMR) systems for both stationary and mobile targets/radar platform. Initially, the orthogonal matching pursuit (OMP)-based mmR (OmMR) algorithm is proposed for stationary targets to estimate their rada...
A sparse channel state information (CSI) estimation model is proposed for reducing the pilot overhead of orthogonal time frequency space (OTFS) modulation aided multiple-input multiple-output (MIMO) systems. Explicitly, the pilots are directly transmitted over the time-frequency (TF)-domain grid for estimating the delay-Doppler (DD)-domain CSI that...
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems relying on sparse channel state information (CSI) estimation techniques is conceived. To begin with, a practical MIMO channel model is developed for the THz band that incorporates its molecular absorption and reflection losses, as well as its non-line-of-sig...
A novel sparse channel state information (CSI) estimation scheme is proposed for orthogonal time frequency space (OTFS) modulated systems, in which the pilots are directly transmitted over the time-frequency (TF)-domain grid for estimating the delay-Doppler (DD)-domain CSI. The proposed CSI estimation model leads to a reduction in the pilot overhea...
A novel sparse channel state information (CSI) estimation scheme is proposed for orthogonal time-frequency space (OTFS) modulated systems, in which the pilots are directly transmitted over the time-frequency (TF)-domain grid for estimating the delay-Doppler (DD)-domain CSI. The proposed CSI estimation model leads to a reduction in the pilot overhea...
Optimal linear minimum mean square error (MMSE) transceiver design techniques are proposed for Bayesian learning (BL)-based sparse parameter vector estimation in a multiple-input multiple-output (MIMO) wireless sensor network (WSN). Our proposed transceiver designs rely on majorization theory and hyperparameter estimates obtained from the BL module...
This paper proposes affine-precoded superimposed pilot (SIP) design, followed by channel state information (CSI) estimation techniques for millimeter wave (mmWave) MIMO-OFDM systems. Toward this end, a multiple measurement vector (MMV) sparse Bayesian learning (SBL)-based SIP (MSIP) technique is initially derived to exploit the simultaneous-sparsit...
Sparse, group-sparse and online channel estimation is conceived for millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. We exploit the angular sparsity of the mmWave channel impulse response (CIR) to achieve improved estimation performance. First a sparse Bayesian learning (SBL)-...
This work conceives techniques for the design of linear hybrid precoders toward decentralized parameter estimation in a millimeter wave (mmWave) wireless sensor network (WSN). To achieve this objective, a novel system model is proposed for mmWave WSNs, wherein the sensors pre-process their observations using hybrid baseband and radio frequency (RF)...
This work conceives techniques for the design of hybrid precoders/combiners for optimal bit allocation in frequency selective millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, toward transmission rate maximization. Initially, the optimal fully digital ideal precoder/ combiner d...
Adaptive block-based least-mean squares (BLMS)-based techniques are conceived for channel estimation in wideband millimeter wave (mmWave) hybrid MIMO systems. In this context, a frequency-domain wideband channel estimation model is developed followed by a novel fast BLMS (FBLMS) technique, which has a significantly lower computational complexity th...
Adaptive block-based least-mean squares (BLMS)-based techniques are conceived for channel estimation in single carrier (SC) wideband millimeter wave (mmWave) hybrid MIMO systems. In this context, a frequency-domain channel estimation model is developed for SC wideband systems, followed by a novel fast BLMS (FBLMS) technique, which has a significant...
This paper designs a novel multiple measurement vector (MMV)-based sparse Bayesian learning (MSBL) technique for wideband channel estimation in single-carrier (SC) mmWave hybrid multiple input multiple output (MIMO) systems. The notable features of the proposed technique are that it leverages the simultaneous sparsity innate in the beamspace channe...
We design and analyse filter bank multicarrier (FBMC) offset quadrature amplitude modulation (OQAM)-based millimeter wave (mmWave) hybrid multiple-input multiple-output (MIMO) systems. Furthermore, a novel channel estimation model is conceived for quasi-static mmWave hybrid MIMO-FBMC-OQAM (mmH-MFO) systems that reconfigures the radio-frequency (RF)...
Semi-blind (SB) channel estimation is conceived for millimeter wave (mmWave) analog-beamforming (AB) and hybrid-beamforming (HB)-based multiple-input multiple-output (MIMO) systems, which also exploits the data symbols for improving the estimation accuracy. A novel aspect of the proposed framework is that it directly estimates the analog beamformer...
Hierarchical Bayesian Kalman filter (HBKF) based schemes are conceived for doubly-selective sparse channel estimation in orthogonal space-time block coded (OSTBC) multipleinput multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless systems. Initially, a pilot based multiple measurement vector (MMV) model is formulated for...
This paper develops schemes for block-sparse channel estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems that exploit the spatial sparsity inherent in such channels. Initially, a novel sparse Bayesian learning (SBL) based block-sparse channel estimation technique is developed for a mmWave hybrid MIMO system with mul...