Dheeraj Naidu Amudala

Bio: Dheeraj Naidu Amudala is an academic researcher from Indian Institute of Technology Kanpur. The author has contributed to research in topics: Computer science & MIMO. The author has an hindex of 2, co-authored 12 publications receiving 13 citations.

Full-Duplex Cell-Free Massive MIMO Systems: Analysis and Decentralized Optimization

Abstract: 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.

UAV-Enabled Hardware-Impaired Spatially Correlated Cell-Free Massive MIMO Systems: Analysis and Energy Efficiency Optimization

Abstract: We consider a cell-free (CF) massive multi-input multi-output (mMIMO) system, where multi-antenna access points (APs) serve single-antenna unmanned aerial vehicles (UAVs) and ground users (GUEs). We assume, unlike the existing CF mMIMO literature, hardware-impaired UAVs and GUEs, which observe a mixture of spatially-correlated Rician- and Rayleigh-faded channels while communicating with hardware-impaired APs. We derive a closed-form downlink spectral efficiency (SE) expression by using practical models for the channel mixture, and by considering channel estimation errors. We propose a novel block quadratic transformation (block-QT) technique to optimize non-convex network-centric global energy efficiency (GEE) by appropriately modeling circuit, UAV propulsion and fronthaul powers. The novel block-QT approach combines block optimization and quadratic transformation technique to decompose GEE optimization into simpler convex sub-problems. We numerically show that i) it is better to operate a UAV at a larger height when it has severe hardware impairments; and ii) when UAVs operate at a lower height, they do not significantly affect the SE of GUEs.

Spectral Efficiency Optimization of Spatially-Correlated Multi-Pair Full-Duplex Massive MIMO Relaying

Abstract: We consider a multi-pair two-way full-duplex (FD) amplify-and-forward relaying, where multiple FD multi-input multi-output (MIMO) users exchange information via a shared FD massive MIMO relay. We derive a closed-form spectral efficiency (SE) lower-bound for maximal-ratio combining/maximal-ratio transmission relay processing considering spatially correlated relay and user antennas, which most of the existing works have ignored. The derived SE lower-bound is applicable for arbitrary number of relay antennas, and simplifies to the following results available in the literature i) the asymptotic SE for number of relay antennas tending to infinity; and ii) the SE lower-bound with independent relay antennas and single-antenna users. We use this SE lower-bound to maximize the non-convex SE, which is of matrix fractional form. We optimize SE by approximating it as concave-convex function, and then by applying matrix quadratic transformation. We numerically validate the SE lower-bound for various system configurations and also characterize their performance for different spatial correlation and interference values. We investigate the gains achieved by the optimal SE over equal power allocation.

Energy Efficiency Optimization of Massive MIMO FD Relay With Quadratic Transform

Abstract: We optimize the weighted sum energy efficiency (WSEE) of two-way amplify and forward relaying, where multiple full-duplex (FD) user-pairs exchange information via a shared FD massive multiple-input multiple-output (MIMO) relay. Optimization of user-centric WSEE metric, which prioritizes links of users with high energy efficiency (EE) requirements by suitably choosing their weights, is a non-convex problem due to its sum-of-ratio form. We optimize it by first approximating WSEE as a concave-convex fractional function, and then by using the quadratic transform. We then use Karush-Kuhn-Tucker (KKT) conditions to derive a closed-form solution to optimize WSEE. We numerically show that the i) proposed solutions achieve significant WSEE gains; and ii) suitable choice of weights can help prioritize EE requirements of different users.

Spatially-Correlated Rician-Faded Multi-Relay Multi-Cell Massive MIMO NOMA Systems

Abstract: We consider the downlink of a relay-aided multi-cell massive multi-input multi-output (mMIMO) system, where in each cell the base station (BS) serves its users via multiple relays by employing non-orthogonal multiple access (NOMA). We model this system by considering spatially-correlated Rician-faded channels and their estimation errors. The users, consequently, perform imperfect successive interference cancellation (SIC). We derive a lower bound on the spectral efficiency (SE) of this system. We then optimize the non-convex global energy efficiency (GEE) metric, which is a fractional function of the optimization variables. We solve this problem by considering a low-complexity alternating minimization maximization approach, which splits a complex joint problem into multiple simpler convex surrogate sub-problems. We propose a novel surrogate function to exploit this framework, and analytically show that it satisfies the desirable properties of a valid surrogate function. We numerically show that 1) reusing the pilots in each cell, when the channel has sufficiently hardened, provides higher SE than using orthogonal pilots in all cells and 2) the proposed GEE algorithm provides similar GEE as that of an existing joint optimization framework, but with much less complexity.

Nonlinear Fractional Programming

Abstract: In this chapter we deal with the following nonlinear fractional programming problem: $$P:\mathop{{\max }}\limits_{{x \in s}} q(x) = (f(x) + \alpha )/((x) + \beta )$$ where f, g: R n → R, α, β ∈ R, S ⊆ R n . To simplify things, and without restricting the generality of the problem, it is usually assumed that, g(x) + β + 0 for all x ∈ S,S is non-empty and that the objective function has a finite optimal value.

Estimation theory

Abstract: Statistical Inference – methods by which generalizations are made about a population Two Major Areas of Statistical Inference 1. Estimation – a parameter is established based on the sampling distribution of a proportion, establishing a certain degree of accuracy from the estimate 2. Test of Hypothesis – a decision is arrived at about a prestated hypothesis, thereby accepting or rejecting the hypothesis.

On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds

Abstract: Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified to stimulate the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed.

Spatially Correlated Massive MIMO Relay Systems With Low-Resolution ADCs

Abstract: In this paper, we investigate the massive MIMO relay system, where the relay station (RS) forwards the signals from multiple remote users to the base station (BS). Large-scale antenna arrays in conjunction with low-resolution analog-to-digital converters (ADCs) are equipped at the RS and the BS to guarantee the high spectral efficiency with low cost. Considering the ever-present spatial correlation at both the RS and the BS, we first study the canonical channel estimation process, from which a tractable equivalent form of the channel estimate is extracted for further analysis. Under these transmission impairments along with the ADC quantization imperfection, we derive the closed-form approximation of the achievable rate. Then the impacts of power scaling, spatial correlation level, and ADC resolution bits are revealed comprehensively to guide the practical system deployment and implementation. Numerical results are presented to verify the theoretical analysis in a straightforward way.

Impacts of Imperfect CSI and Transceiver Hardware Noise on the Performance of Full-Duplex DF Relay System With Multi-Antenna Terminals Over Nakagami- m Fading Channels

Abstract: In this paper, we investigate the performance of a full-duplex (FD) relay system where multi-antennas are exploited at source and destination. Unlike previous works, the impacts of imperfect channel state information (I-CSI), transceiver hardware noise (THN), and residual self-interference (RSI) are taken into account. We mathematically derive the exact closed-form expressions of the outage probability (OP), symbol error rate (SER), and ergodic capacity (EC) of the FD relay system with I-CSI, THN, and RSI over Nakagami- $m$ fading channels. From the derived expressions, the performance of the considered system under the effects of three negative factors (I-CSI, THN, and RSI) is compared with that system in the case of all ideal factors (perfect channel state information (P-CSI), perfect transceiver hardware (P-TH) and perfect self-interference cancellation (P-SIC)), two ideal factors (P-CSI and P-TH, P-CSI and P-SIC, P-TH and P-SIC), or one ideal factor (P-CSI or P-TH or P-SIC). Numerical results show a strong impact of three negative factors on the OP, SER, and EC of the considered FD relay system, especially when the data transmission rate of the system and signal-to-noise ratio (SNR) are high. In particular, OP, SER, and EC go to the floors in the high SNR regime due to the three negative factors. Therefore, when I-CSI, THNs, and RSI exist in the FD relay system, we should use suitable source and relay transmission power to obtain excellent performance while saving energy consumption. Moreover, when two of the three negative factors are large enough, the remaining factor’s impact becomes weaker and may be neglected in certain circumstances.