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Narayan Prasad

Publications and source records attributed to Narayan Prasad.

14 recordsLinked to original sources

Reconfigurable Intelligent Surface: Design the Channel -- a New Opportunity for Future Wireless Networks

In this paper, we survey state-of-the-art research outcomes in the burgeoning field of reconfigurable intelligent surface (RIS) in view of its potential for significant performance enhancement for next generation wireless communication networks by means of adapting the propagation environment. Emphasis has been placed on several aspects gating the commercially viability of a future network deployment. Comprehensive summaries are provided for practical hardware design considerations and broad implications of artificial intelligence techniques, so are in-depth outlooks on salient aspects of system models, use cases, and physical layer optimization techniques.

eess.SP

Base Station Antenna Selection for Low-Resolution ADC Systems

This paper investigates antenna selection at a base station with large antenna arrays and low-resolution analog-to-digital converters. For downlink transmit antenna selection for narrowband channels, we show (1) a selection criterion that maximizes sum rate with zero-forcing precoding equivalent to that of a perfect quantization system; (2) maximum sum rate increases with number of selected antennas; (3) derivation of the sum rate loss function from using a subset of antennas; and (4) unlike high-resolution converter systems, sum rate loss reaches a maximum at a point of total transmit power and decreases beyond that point to converge to zero. For wideband orthogonal-frequency-division-multiplexing (OFDM) systems, our results hold when entire subcarriers share a common subset of antennas. For uplink receive antenna selection for narrowband channels, we (1) generalize a greedy antenna selection criterion to capture tradeoffs between channel gain and quantization error; (2) propose a quantization-aware fast antenna selection algorithm using the criterion; and (3) derive a lower bound on sum rate achieved by the proposed algorithm based on submodular functions. For wideband OFDM systems, we extend our algorithm and derive a lower bound on its sum rate. Simulation results validate theoretical analyses and show increases in sum rate over conventional algorithms.

eess.SP

New equivalent model of quantizer with noisy input and its application for ADC resolution determination in an uplink MIMO receiver

When a quantizer input signal is the sum of the desired signal and input white noise, the quantization error is a function of total input signal. Our new equivalent model splits the quantization error into two components: a non-linear distortion (NLD) that is a function of only the desired part of input signal (without noise), and an equivalent out-put white noise. This separation is important because these two terms affect MIMO system performance differently. This paper introduces our model, and applies it to determine the minimal Analog-to-Digital Converter (ADC) resolution necessary to operate a conventional MIMO receiver with negligible performance degradation. We also provide numerical simulations to confirm the theory. Broad ramifications of our model are further demonstrated in two companion papers presenting low-complexity suppression of the NLD arising from insufficient ADC resolution, and a digital dithering that significantly reduces the MIMO transmitter Digital-to-Analog Converters (DAC) resolution requirement.

cs.NI

Optimizing Beams and Bits: A Novel Approach for Massive MIMO Base-Station Design

We consider the problem of jointly optimizing ADC bit resolution and analog beamforming over a frequency-selective massive MIMO uplink. We build upon a popular model to incorporate the impact of low bit resolution ADCs, that hitherto has mostly been employed over flat-fading systems. We adopt weighted sum rate (WSR) as our objective and show that WSR maximization under finite buffer limits and important practical constraints on choices of beams and ADC bit resolutions can equivalently be posed as constrained submodular set function maximization. This enables us to design a constant-factor approximation algorithm. Upon incorporating further enhancements we obtain an efficient algorithm that significantly outperforms state-of-the-art ones.

eess.SP

Exploiting Dual Connectivity in Heterogeneous Cellular Networks

We consider network utility maximization problems over heterogeneous cellular networks (HetNets) that permit dual connectivity. Dual connectivity (DC) is a feature that targets emerging practical HetNet deployments that will comprise of non-ideal (higher latency) connections between transmission nodes, and has been recently introduced to the LTE-Advanced standard. DC allows for a user to be simultaneously served by a macro node as well as one other (typically micro or pico) node and requires relatively coarser level coordination among serving nodes. For such a DC enabled HetNet we comprehensively analyze the problem of determining an optimal user association, where in any feasible association each user can be associated with (i.e., configured to receive data from) any one macro node (in a given set of macro nodes) and any one pico node that lies in the chosen macro node's coverage area. We consider the weighted sum rate system utility subject to per-user maximum and minimum rate constraints, as well as the proportional fairness (PF) system utility. For both utility choices we construct approximation algorithms and establish their respective approximation guarantees. We then validate the performance of our algorithms via numerical results.

cs.NI

Optimizing User Association and Activation Fractions in Heterogeneous Wireless Networks

We consider the problem of maximizing the alpha-fairness utility over the downlink of a heterogeneous wireless network (HetNet) by jointly optimizing the association of users to transmission points (TPs) and the activation fractions of all TPs. Activation fraction of each TP is the fraction of the frame duration for which it is active, and together these fractions influence the interference seen in the network. To address this joint optimization problem we adopt an approach wherein the activation fractions and the user associations are optimized in an alternating manner. The sub-problem of determining the optimal activation fractions is solved using an auxiliary function method that we show is provably convergent and is amenable to distributed implementation. On the other hand, the sub-problem of determining the user association is solved via a simple combinatorial algorithm. Meaningful performance guarantees are derived and a distributed variant offering identical guarantees is also proposed. The significant benefits of using the proposed algorithms are then demonstrated via realistic simulations.

cs.NI

AADNMR: A Simple Method for Rapid Identification of Bacterial/Mycobacterial Infections in Antibiotic Treated Peritoneal Dialysis Effluent Samples for Diagnosis of Infectious Peritonitis

An efficient method is reported for rapid identification of bacterial or mycobacterial infection in a suspected clinical/biological sample. The method is based on the fact that the ring methylene protons of cyclic fatty acids (constituting the cell membrane of several species of bacteria and mycobacteria) resonate specifically between -0.40 and 0.68 ppm region of the 1H NMR spectrum. These cyclic fatty acids are rarely found in the eukaryotic cell membranes. Therefore, the signals from cyclic ring moiety of these fatty acids can be used as markers (a) for the identification of bacterial and mycobacterial infections and (b) for differential diagnosis of bacterial and fungal infections. However, these microbial fatty acids when present inside the membrane are not easily detectable by NMR owing to their fast T2 relaxation. Nonetheless, the problem can easily be circumvented if these fatty acids become suspended in solution. This has been achieved by abolishing the membrane integrity using broad spectrum antibiotics (including ampicillin). The suspended fatty acids are then detected by NMR to probe the infection. Therefore, the method has been given the name AADNMR i.e. Add Antibiotic to Detect by NMR. The method has been tested here using both Gram positive and Gram negative bacterial strains and finally the utility of method is demonstrated for discriminating bacterial and fungal infections to aid timely diagnosis of infectious peritonitis (a life threatening complication associated with prolonged peritoneal dialysis).

physics.bio-ph

Metabolite Characterization in Peritoneal Dialysis Effluent Using High-resolution 1H and 1H-13C NMR Spectroscopy

Metabolite analysis of peritoneal dialysis (PD) effluent may provide information regarding onset and progression of complications associated with prolonged PD therapy. In this context, the NMR detectable small metabolites of PD effluent samples were characterized using high resolution 1H and 1H-13C NMR spectroscopy. The various spectra were recorded (at 800 MHz proton frequency) on PD effluent samples obtained after 4 hour (intraperitoneal) dwell time from patients with end stage renal failure (ESRF) and continuing normally on PD therapy. Inspite of devastating spectral feature of PD effluent due to the presence of intense resonances from glucose and lactate, we were able to identify about 53 small endogenous metabolites (including many complex coupled spin systems) and more than 90 % of the total CH cross peaks of 1H-13C HSQC spectrum were identified specific to various metabolites of PD effluent. We foresee that the characteristic fingerprints of various metabolites of control PD effluent samples will be used to identify and distinguish metabolic differences from PD related complications.

physics.bio-ph

Multi-User Scheduling in the 3GPP LTE Cellular Uplink

In this paper, we consider resource allocation in the 3GPP Long Term Evolution (LTE) cellular uplink, which will be the most widely deployed next generation cellular uplink. The key features of the 3GPP LTE uplink (UL) are that it is based on a modified form of the orthogonal frequency division multiplexing based multiple access (OFDMA) which enables channel dependent frequency selective scheduling, and that it allows for multi-user (MU) scheduling wherein multiple users can be assigned the same time-frequency resource. In addition to the considerable spectral efficiency improvements that are possible by exploiting these two features, the LTE UL allows for transmit antenna selection together with the possibility to employ advanced receivers at the base-station, which promise further gains. However, several practical constraints that seek to maintain a low signaling overhead, are also imposed. In this paper, we show that the resulting resource allocation problem is APX-hard and then propose a local ratio test (LRT) based constant-factor polynomial-time approximation algorithm. We then propose two enhancements to this algorithm as well as a sequential LRT based MU scheduling algorithm that offers a constant-factor approximation and is another useful choice in the complexity versus performance tradeoff. Further, user pre-selection, wherein a smaller pool of good users is pre-selected and a sophisticated scheduling algorithm is then employed on the selected pool, is also examined. We suggest several such user pre-selection algorithms, some of which are shown to offer constant-factor approximations to the pre-selection problem. Detailed evaluations reveal that the proposed algorithms and their enhancements offer significant gains.

cs.NI

Multi-User MIMO Scheduling in the Fourth Generation Cellular Uplink

We consider Multi-User MIMO (MU-MIMO) scheduling in the 3GPP LTE-Advanced (3GPP LTE-A) cellular uplink. The 3GPP LTE-A uplink allows for precoded multi-stream (precoded MIMO) transmission from each scheduled user and also allows flexible multi-user (MU) scheduling wherein multiple users can be assigned the same time-frequency resource. However, exploiting these features is made challenging by certain practical constraints that have been imposed in order to maintain a low signaling overhead. We show that while the scheduling problem in the 3GPP LTE-A cellular uplink is NP-hard, it can be formulated as the maximization of a submodular set function subject to one matroid and multiple knapsack constraints. We then propose constant-factor polynomial-time approximation algorithms and demonstrate their superior performance via simulations.

cs.NI

Exploiting Hybrid Channel Information for Downlink Multi-User MIMO Scheduling

We investigate the downlink multi-user MIMO (MU-MIMO) scheduling problem in the presence of imperfect Channel State Information at the transmitter (CSIT) that comprises of coarse and current CSIT as well as finer but delayed CSIT. This scheduling problem is characterized by an intricate `exploitation - exploration tradeoff' between scheduling the users based on current CSIT for immediate gains, and scheduling them to obtain finer albeit delayed CSIT and potentially larger future gains. We solve this scheduling problem by formulating a frame based joint scheduling and feedback approach, where in each frame a policy is obtained as the solution to a Markov Decision Process. We prove that our proposed approach can be made arbitrarily close to the optimal and then demonstrate its significant gains over conventional MU-MIMO scheduling.

cs.IT

Precoder Design for Physical Layer Multicasting

This paper studies the instantaneous rate maximization and the weighted sum delay minimization problems over a K-user multicast channel, where multiple antennas are available at the transmitter as well as at all the receivers. Motivated by the degree of freedom optimality and the simplicity offered by linear precoding schemes, we consider the design of linear precoders using the aforementioned two criteria. We first consider the scenario wherein the linear precoder can be any complex-valued matrix subject to rank and power constraints. We propose cyclic alternating ascent based precoder design algorithms and establish their convergence to respective stationary points. Simulation results reveal that our proposed algorithms considerably outperform known competing solutions. We then consider a scenario in which the linear precoder can be formed by selecting and concatenating precoders from a given finite codebook of precoding matrices, subject to rank and power constraints. We show that under this scenario, the instantaneous rate maximization problem is equivalent to a robust submodular maximization problem which is strongly NP hard. We propose a deterministic approximation algorithm and show that it yields a bicriteria approximation. For the weighted sum delay minimization problem we propose a simple deterministic greedy algorithm, which at each step entails approximately maximizing a submodular set function subject to multiple knapsack constraints, and establish its performance guarantee.

cs.IT

Robust Linear Precoder Design for Multi-cell Downlink Transmission

Coordinated information processing by the base stations of multi-cell wireless networks enhances the overall quality of communication in the network. Such coordinations for optimizing any desired network-wide quality of service (QoS) necessitate the base stations to acquire and share some channel state information (CSI). With perfect knowledge of channel states, the base stations can adjust their transmissions for achieving a network-wise QoS optimality. In practice, however, the CSI can be obtained only imperfectly. As a result, due to the uncertainties involved, the network is not guaranteed to benefit from a globally optimal QoS. Nevertheless, if the channel estimation perturbations are confined within bounded regions, the QoS measure will also lie within a bounded region. Therefore, by exploiting the notion of robustness in the worst-case sense some worst-case QoS guarantees for the network can be asserted. We adopt a popular model for noisy channel estimates that assumes that estimation noise terms lie within known hyper-spheres. We aim to design linear transceivers that optimize a worst-case QoS measure in downlink transmissions. In particular, we focus on maximizing the worst-case weighted sum-rate of the network and the minimum worst-case rate of the network. For obtaining such transceiver designs, we offer several centralized (fully cooperative) and distributed (limited cooperation) algorithms which entail different levels of complexity and information exchange among the base stations.

cs.IT

Beamforming and Rate Allocation in MISO Cognitive Radio Networks

We consider decentralized multi-antenna cognitive radio networks where secondary (cognitive) users are granted simultaneous spectrum access along with license-holding (primary) users. We treat the problem of distributed beamforming and rate allocation for the secondary users such that the minimum weighted secondary rate is maximized. Such an optimization is subject to (1) a limited weighted sum-power budget for the secondary users and (2) guaranteed protection for the primary users in the sense that the interference level imposed on each primary receiver does not exceed a specified level. Based on the decoding method deployed by the secondary receivers, we consider three scenarios for solving this problem. In the first scenario each secondary receiver decodes only its designated transmitter while suppressing the rest as Gaussian interferers (single-user decoding). In the second case each secondary receiver employs the maximum likelihood decoder (MLD) to jointly decode all secondary transmissions, and in the third one each secondary receiver uses the unconstrained group decoder (UGD). By deploying the UGD, each secondary user is allowed to decode any arbitrary subset of users (which contains its designated user) after suppressing or canceling the remaining users.

cs.IT