References of "Bandi, Ashok 50027307"
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See detailA RAN Resource Slicing Mechanism for Multiplexing of eMBB and URLLC Services in OFDMA based 5G Wireless Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in IEEE Access (2020)

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two ... [more ▼]

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two services on the same wireless infrastructure leads to a challenging resource allocation problem due to their heterogeneous specifications. To address this problem, slicing has emerged as an architecture that enables a logical network with specific radio access functionality to each of the supported services on the same network infrastructure. The allocation of radio resources to each slice according to their requirements is a fundamental part of the network slicing that is usually executed at the radio access network (RAN). In this work, we formulate the RAN resource allocation problem as a sum-rate maximization problem subject to the orthogonality constraint (i.e., service isolation), latency-related constraint and minimum rate constraint while maintaining the reliability constraint with the incorporation of adaptive modulation and coding (AMC). However, the formulated problem is not mathematically tractable due to the presence of a step-wise function associated with the AMC and a binary assignment variable. Therefore, to solve the proposed optimization problem, first, we relax the mathematical intractability of AMC by using an approximation of the non-linear AMC achievable throughput, and next, the binary constraint is relaxed to a box constraint by using the penalized reformulation of the problem. The result of the above two-step procedure provides a close-to-optimal solution to the original optimization problem. Furthermore, to ease the complexity of the optimization-based scheduling algorithm, a low-complexity heuristic scheduling scheme is proposed for the efficient multiplexing of URLLC and eMBB services. Finally, the effectiveness of the proposed optimization and heuristic schemes is illustrated through extensive numerical simulations. [less ▲]

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See detailJoint Scheduling and Precoding for Frame-Based Multigroup Multicasting in Satellite Communications
Bandi, Ashok UL; Shankar, Bhavani UL; Chatzinotas, Symeon UL et al

in Bandi, Ashok; Shankar, Bhavani; Chatzinotas, Symeon (Eds.) et al Joint Scheduling and Precoding for Frame-Based Multigroup Multicasting in Satellite Communications (2019, December 09)

Recent satellite standards enforce the coding of multiple users’ data in a frame. This transmission strategy mimics the well-known physical layer multigroup multicasting (MGMC). However, typical beam ... [more ▼]

Recent satellite standards enforce the coding of multiple users’ data in a frame. This transmission strategy mimics the well-known physical layer multigroup multicasting (MGMC). However, typical beam coverage with a large number of users and limited frame length lead to the scheduling of only a few users. Moreover, in emerging aggressive frequency reuse systems, scheduling is coupled with precoding. This is addressed in this work, through the joint design of scheduling and precoding for frame-based MGMC satellite systems. This aim is formulated as the maximization of the sum-rate under per beam power constraint and minimum SINR requirement of scheduled users. Further, a framework is proposed to transform the non-smooth SR objective with integer scheduling and nonconvex SINR constraints as a difference-of-convex problem that facilitates the joint update of scheduling and precoding. Therein, an efficient convex-concave procedure based algorithm is proposed. Finally, the gains (up to 50%) obtained by the jointed design over state-of-the-art methods is shown through Monte-Carlo simulations. [less ▲]

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See detailMultigroup Multicast Precoding for Energy Optimization in SWIPT Systems with Heterogeneous Users
Gautam, Sumit UL; Lagunas, Eva UL; Bandi, Ashok UL et al

in IEEE Communications Society Magazine (2019)

The key to developing future generations of wireless communication systems lies in the expansion of extant methodologies, which ensures the coexistence of a variety of devices within a system. In this ... [more ▼]

The key to developing future generations of wireless communication systems lies in the expansion of extant methodologies, which ensures the coexistence of a variety of devices within a system. In this paper, we assume several multicasting (MC) groups comprising three types of heterogeneous users including Information Decoding (ID), Energy Harvesting (EH) and both ID and EH. We present a novel framework to investigate the multi-group (MG) - MC precoder designs for three different scenarios, namely, Separate Multicast and Energy Precoding Design (SMEP), Joint Multicast and Energy Precoding Design (JMEP), and Per-User Information and/or Energy Precoding Design (PIEP). In the considered system, a multi-antenna source transmits the relevant information and/or energy to the groups of corresponding receivers using more than one MC streams. The data processing users employ the conventional ID receiver architectures, the EH users make use of a non-linear EH module for energy acquisition, while the users capable of performing both ID and EH utilize the separated architecture with disparate ID and non-linear EH units. Our contribution is threefold. Firstly, we propose an optimization framework to i) minimize the total transmit power and ii) to maximize the sum harvested energy, the two key performance metrics of MG-MC systems. The proposed framework allows the analysis of the system under arbitrary given quality of service and harvested energy requirements. Secondly, to deal with the non-convexity of the formulated problems, we transform the original problems respectively into equivalent forms, which can be effectively solved by semi-definite relaxation (SDR) and alternating optimization. The convergence of the proposed algorithms is analytically guaranteed. Thirdly, a comparative study between the proposed schemes is conducted via extensive numerical results, wherein the benefits of adopting SMEP over JMEP and PIEP models are discussed [less ▲]

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See detailA Joint Solution for Scheduling and Precoding in Multiuser MISO Downlink Channels
Bandi, Ashok UL; Shankar, Bhavani UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2019)

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See detailA Novel Approach to Joint User Selection and Precoding for Multiuser MISO Downlink Channels
Bandi, Ashok UL; Shankar, Bhavani UL; Chatzinotas, Symeon UL et al

in Bandi, Ashok; Shankar, Bhavani; maleki, Sina (Eds.) et al 6th IEEE Global Conference on Signal and Information Processing, November 26–29, 2018 Anaheim, California, USA (2018, November 26)

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See detailSparsity-Aided Low-Implementation cost based On-Board beamforming Design for High Throughput Satellite Systems
Bandi, Ashok UL

in Bandi, Ashok; Joroughi, Vahid; Shankar, Bhavani (Eds.) et al 9th Advanced Satellite Multimedia Systems Conference (ASMS) and 15th Signal Processing for Space Communications Workshop (SPSC),Berlin, Sept. 10-12, 2018 (2018, September 10)

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See detailStructured Sparse Recovery Algorithms for Data Decoding in Media Based Modulation
Bandi, Ashok UL; Murthy, Chandra

in International Conference on Communications, Paris 21-25 May 2017 (2017, May 21)

Detailed reference viewed: 70 (3 UL)