arXiv subjects

Rohit Budhiraja

Publications and source records attributed to Rohit Budhiraja.

14 recordsLinked to original sources

arXiv2026

Is Downlink Training Necessary for User-Centric Cell-Free RSMA Systems With Mobile Users?

We study the spectral efficiency (SE) of a ratesplitting multiple access (RSMA) enabled multi-clustered cell-free (CF) massive multiple-input multiple-output (mMIMO) system. The access points (APs) in each cluster serve mobile user equipments (UEs) by employing RSMA. The UEs employ successive interference cancellation to decode their data. This work emphasizes the role of downlink (DL) pilots in realizing RSMA benefits in practical CF systems with spatially-correlated Rician channels which observe random phase shifts, pilot contamination, and channel aging due to UE mobility. We numerically show that DL pilots are required for RSMA in user-centric CF mMIMO systems with channel aging to outperform spatial division multiple access. We show that the degraded channel quality due to higher UE velocity and longer resource block lengths significantly reduces the RSMA SE. Increasing the number of clusters can compensate for the SE loss.

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arXiv2024

Multi-cell mMIMO IRS Systems With Impairments and Aging: Phase Optimization and Receiver Design

We consider the uplink of a hardware-impaired intelligent reflective surfaces (IRS) aided multi-cell massive multiple-input multiple-output (mMIMO) system with mobile user equipments, whose channel age with time. For this system, we analyze the distortion due to hardware impairments, and the effect of channel aging, and propose a novel distortion-and-aging-aware MMSE (DAA-MMSE) receiver that not only provides a higher spectral efficiency (SE) than conventional maximal ratio and distortion-unaware MMSE (DU-MMSE) receivers, but also reduces the pilot overhead. By considering non-ideal hardware and spatially-correlated Rician fading channels with phase shifts, we also derive the SE lower bound for this system. We show that the SE gain of the DAA-MMSE receiver over DU-MMSE receiver increases with hardware impairments, and channel aging. Along with DAA-MMSE receiver, the IRS is also shown to reduce the pilot overhead in a mMIMO system with channel aging.

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arXiv2023

Hardware-Impaired Rician-Faded Cell-Free Massive MIMO Systems With Channel Aging

We study the impact of channel aging on the uplink of a cell-free (CF) massive multiple-input multiple-output (mMIMO) system by considering i) spatially-correlated Rician-faded channels; ii) hardware impairments at the access points and user equipments (UEs); and iii) two-layer large-scale fading decoding (LSFD). We first derive a closed-form spectral efficiency (SE) expression for this system, and later propose two novel optimization techniques to optimize the non-convex SE metric by exploiting the minorization-maximization (MM) method. The first one requires a numerical optimization solver, and has a high computation complexity. The second one with closed-form transmit power updates, has a trivial computation complexity. We numerically show that i) the two-layer LSFD scheme effectively mitigates the interference due to channel aging for both low- and high-velocity UEs; and ii) increasing the number of AP antennas does not mitigate the SE deterioration due to channel aging. We numerically characterize the optimal pilot length required to maximize the SE for various UE speeds. We also numerically show that the proposed closed-form MM optimization yields the same SE as that of the first technique, which requires numerical solver, and that too with a much reduced time-complexity.

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arXiv2023

LSFD for Rician-Faded Cell-Free mMIMO Systems With Channel Aging and Hardware Impairments

We study the impact of channel aging on the uplink of a cell-free massive multiple-input multiple-output system with hardware impairments. We consider a dynamic analog-to-digital converter architecture at the access points (APs), and low-resolution digital-to-analog converters at the user equipments (UEs). We derive a closed-form spectral efficiency expression by considering i) practical spatially-correlated Rician channels; ii) hardware impairments at the APs and the UEs; iii) channel aging; and iv) large-scale fading decoding (LSFD). We show that LSFD can effectively mitigate the detrimental effects of i) channel aging for both low and high UE velocities; and ii) inter-user interference for low-velocity UEs but not for high-velocity UEs.

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arXiv2022

Hardware-Aware Pilot Decontamination Precoding for Multi-cell mMIMO Systems With Rician Fading

We consider a hardware-impaired multi-cell Rician faded massive multi-input multi-output (mMIMO) system with two-layer pilot decontamination precoding, also known as large-scale fading precoding (LSFP). Each BS is equipped with a flexible dynamic analog-to-digital converter (ADC)/digital-to-analog converter (DAC) architecture and the user equipments (UEs) have low-resolution ADCs. Further, both BS and UEs have hardwareimpaired radio frequency chains. The dynamic ADC/DAC architecture allows us to vary the resolution of ADC/DAC connected to each BS antenna, and suitably choose them to maximize the SE. We propose a distortion-aware minimum mean squared error (DA-MMSE) precoder and investigate its usage with two-layer LSFP and conventional single-layer precoding (SLP) for hardware-impaired mMIMO systems. We discuss the use cases of LSFP and SLP with DA-MMSE and distortion-unaware MMSE (DU-MMSE) precoders, which will provide critical insights to the system designer regarding their usage in practical systems.

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arXiv2022

Variational Learning Algorithms For Channel Estimation in RIS-assisted mmWave Systems

We consider the problem of estimating the channel in reconfigurable intelligent surface (RIS) assisted millimeter wave (mmWave) systems. We propose two variational expectation maximization (VEM) based algorithms for channel estimation in RIS-aided wireless systems. The first algorithm is a structured mean field-based sparse Bayesian learning (SM-SBL) algorithm that exploits the doubly-structured sparsity and the individual sparsity of the elements of the channel. To exploit the sparsities, we propose a column-wise coupled Gaussian prior. We next design the factorized mean field-based algorithm based on the prior we propose. This algorithm called the factorized mean field SBL (FM-SBL) algorithm, addresses the time complexities of the SM-SBL algorithm without sacrificing channel estimation accuracy. We show using extensive numerical investigations that the i) proposed SM-SBL and FM-SBL algorithms outperform several existing algorithms and ii) FM-SBL has lower time complexity than the SM-SBL algorithm.

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arXiv2021

Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a two-layered approach: the first layer formulates the optimization as a generalized convex program, while the {second layer} solves the optimization decentrally using the alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of the WSEE metric to incorporate heterogeneous EE requirements of users. We show that low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

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arXiv2021

FD Cell-Free mMIMO: Analysis and Optimization

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a {two-layered} approach: the first layer formulates the optimization as a generalized convex program, while the second layer solves the optimization decentrally using alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of WSEE metric to incorporate heterogeneous EE requirements of users. We show that the low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

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arXiv2020

OTFS Channel Estimation And Data Detection Designs With Superimposed Pilots

This work proposes a superimposed pilot (SP)-based channel estimation and data detection framework for orthogonal time-frequency space (OTFS) scheme, wherein low-powered pilots are superimposed on to data symbols in the delay-Doppler domain. We propose two channel estimation and data detection designs for SP-OTFS systems which, unlike the existing OTFS designs, do not designate any slots for pilots, which improves their spectral efficiency (SE). The first SP design estimates channel by treating data as interference, which degrades its performance at high signal to noise ratio. The second SP design alleviates this problem by iterating between channel estimation and data detection. Both these designs detect data using message passing algorithm which exploits OTFS channel sparsity, and consequently has low computational complexity. We also derive a lower bound on the signal-to-interference-plus-noise ratio of the proposed designs, and maximize it by optimally allocating power between data and pilot symbols. We numerically validate the derived analytical results, and show that the proposed designs have superior SE than the two state-of-the-art OTFS channel estimation and data detection designs.

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arXiv2020

Low-Complexity ZF/MMSE Receivers for MIMO-OTFS Systems With Imperfect CSI

Orthogonal time-frequency space (OTFS) scheme, which transforms a time and frequency selective channel into an almost non-selective channel in the delay-Doppler domain, establishes reliable wireless communication for high-speed moving devices. This work designs and analyzes low-complexity zero-forcing (LZ) and minimum mean square error (LM) receivers for multiple-input multiple-output (MIMO)-OTFS systems with perfect and imperfect receive channel state information (CSI). The proposed receivers provide exactly the same solution as that of the conventional counterparts, and reduce the complexity by exploiting the doubly-circulant nature of the MIMO-OTFS channel matrix, the block-wise inverse, and Schur complement. We also derive, by exploiting the Taylor expansion and results from random matrix theory, a tight approximation of the post-processing signal-to-noise-plus-interference-ratio (SINR) expressions in closed-form for both LZ and LM receivers. We show that the derived SINR expressions, when averaged over multiple channel realizations, accurately characterize their respective bit error rate (BER) of both perfect and imperfect receive CSI. We numerically show the lower BER and lower complexity of the proposed designs over state-of-the-art exiting solutions.

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arXiv2018

Hybrid Block Diagonalization for Massive MIMO Two-Way Half-Duplex AF Hybrid Relay

We consider a multi-pair two-way amplify-and-forward massive multi-input multi-output (MIMO) hybrid relay with MIMO user-pairs. A hybrid relay has lesser number of radio frequency (RF) chains than the antennas, which significantly reduces the implementation cost. We employ block-diagonalization-based baseband processing at the hybrid relay to cancel the inter user-pair interference and equal-gain-combining-based RF processing to maximize the beamforming gain. We also use an algebraic norm maximizing relay transmit strategy to maximize the spectral efficiency (SE) of each user-pair. We numerically show that the proposed hybrid relay has only marginally inferior SE than a full RF-chain relay.

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arXiv2017

Full-Duplex Massive MIMO Multi-Pair Two-Way AF Relaying: Energy Efficiency Optimization

We consider two-way amplify and forward relaying, where multiple full-duplex user pairs exchange information via a shared full-duplex massive multiple-input multiple-output (MIMO) relay. Most of the previous massive MIMO relaying works maximize the spectral efficiency (SE). By contrast, we maximize the non-convex energy efficiency (EE) metric by approximating it as a pseudo-concave problem, which is then solved using the classic Dinkelbach approach. We also maximize the EE of the least energy-efficient user {relying} on the max-min approach. For solving these optimization problems, we derive closed-form lower bounds for the ergodic achievable rate both for maximal-ratio combining and zero-forcing processing at the relay, by using minimum mean squared error channel estimation. We numerically characterize the accuracy of the lower bounds derived. We also compare the SE and EE of the proposed design to those of the existing full-duplex systems and quantify the significant improvement achieved by the proposed algorithm. We also compare the EE of the proposed full-duplex system to that of its half-duplex counterparts, and characterize the self-loop and inter-user interference regimes, for which the proposed full-duplex system succeeds in outperforming the half-duplex ones.

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arXiv2017

Multi-Pair Two Way AF Full-Duplex Massive MIMO Relaying with ZFR/ZFT Processing

We consider two-way amplify and forward relaying, where multiple full-duplex user pairs exchange information via a shared full-duplex massive multiple-input multiple-output (MIMO) relay. We derive closed-form lower bound for the spectral efficiency with zero-forcing processing at the relay, by using minimum mean squared error channel estimation. The zero-forcing lower bound for the system model considered herein, which is valid for arbitrary number of antennas, is not yet derived in the massive MIMO relaying literature. We numerically demonstrate the accuracy of the derived lower bound and the performance improvement achieved using zero-forcing processing. We also numerically demonstrate the spectral gains achieved by a full-duplex system over a half-duplex one for various antenna regimes.

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arXiv2013

Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems

Two-way relaying (TWR) reduces the spectral-efficiency loss caused in conventional half-duplex relaying. TWR is possible when two nodes exchange data simultaneously through a relay. In cellular systems, data exchange between base station (BS) and users is usually not simultaneous e.g., a user (TUE) has uplink data to transmit during multiple access (MAC) phase, but does not have downlink data to receive during broadcast (BC) phase. This non-simultaneous data exchange will reduce TWR to spectrally-inefficient conventional half-duplex relaying. With infrastructure relays, where multiple users communicate through a relay, a new transmission protocol is proposed to recover the spectral loss. The BC phase following the MAC phase of TUE is now used by the relay to transmit downlink data to another user (RUE). RUE will not be able to cancel the back-propagating interference. A structured precoder is designed at the multi-antenna relay to cancel this interference. With multiple-input multiple-output (MIMO) nodes, the proposed precoder also triangulates the compound MAC and BC phase MIMO channels. The channel triangulation reduces the weighted sum-rate optimization to power allocation problem, which is then cast as a geometric program. Simulation results illustrate the effectiveness of the proposed protocol over conventional solutions.

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