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Chandan Kumar Sheemar

Publications and source records attributed to Chandan Kumar Sheemar.

43 records · Page 3Linked to original sources

Robust Beamforming for IRS Aided MIMO Full Duplex Systems

In this paper, a novel robust beamforming for an intelligent reflecting surface (IRS) assisted FD system is presented. Since perfect channel state information (CSI) is often challenging to acquire in practice, we consider the case of imperfect CSI and adopt a statistically robust beamforming approach to maximize the ergodic weighted sum rate (WSR). We also analyze the achievable WSR of an IRS-assisted FD with imperfect CSI, for which the lower and the upper bounds are derived. The ergodic WSR maximization problem is tackled based on the expected Weighted Minimum Mean Squared Error (WMMSE), which is guaranteed to converge to a local optimum. The effectiveness of the proposed design is investigated with extensive simulation results. It is shown that our robust design achieves significant performance gain compared to the naive beamforming approaches and considerably outperforms the robust Half-Duplex (HD) system.

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Full-Duplex-Enabled Joint Communications and Sensing with Reconfigurable Intelligent Surfaces

The full-duplex (FD) technology has the potential to radically evolve wireless systems, facilitating the integration of both communications and radar functionalities into a single device, thus, enabling joint communication and sensing (JCAS). In this paper, we present a novel approach for JCAS that incorporates a reconfigurable intelligent surface (RIS) in the near-field of an FD multiple-input multiple-output (MIMO) node, which is jointly optimized with the digital beamformers to enable JSAC and efficiently handle self-interference (SI). We propose a novel problem formulation for FD MIMO JCAS systems to jointly minimize the total received power at the FD node's radar receiver while maximizing the sum rate of downlink communications subject to a Cramér-Rao bound (CRB) constraint. In contrast to the typically used CRB in the relevant literature, we derive a novel, more accurate, target estimation bound that fully takes into account the RIS deployment. The considered problem is solved using alternating optimization, which is guaranteed to converge to a local optimum. The simulation results demonstrate that the proposed scheme achieves significant performance improvement both for communications and sensing. It is showcased that, jointly designing the FD MIMO beamformers and the RIS phase configuration to be SI aware can significantly loosen the requirement for additional SI cancellation.

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Intelligent Reflecting Surfaces Assisted Millimeter Wave MIMO Full Duplex Systems

Full duplex (FD) systems suffer from very high hardware cost and high power consumption to mitigate the self-interference (SI) in the analog domain. Moreover, in millimeter wave (mmWave) they rely on hybrid beamforming (HYBF) as a signal processing tool to partially deal with the SI, which presents many drawbacks such as high insertion loss and high power consumption. This article proposes the use of near-field (NF-) IRSs for FD systems with the objective to solve the aforementioned issues cost-efficiently. Namely, we propose to truncate the analog/hybrid beamforming stage of the mmWave FD systems and compensate it with an NF-IRS, to simultaneously and smartly control the uplink (UL) and downlink (DL) channels, while assisting in shaping the SI channel: this to obtain very strong passive SI cancellation. A novel joint active and passive beamforming design for the weighted sum-rate (WSR) maximization of a NF-IRS-assisted mmWave point-to-point FD system is presented. Results show that the proposed solution fully reaps the benefits of the IRSs only when they operate in the NF, which leads to considerably higher gains compared to the conventional massive MIMO (mMIMO) mmWave FD and half duplex (HD) systems.

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Parallel and Distributed Hybrid Beamforming for Multicell Millimeter Wave MIMO Full Duplex

Full duplex (FD) is an auspicious wireless technology that holds the potential to double data rates through simultaneous transmission and reception. This paper proposes two innovative designs of hybrid beamforming (HYBF) for a multicell massive multiple-input-multiple-output (mMIMO) millimeter wave (mmWave) FD system. Initially, we introduce a novel centralized HYBF (C-HYBF) scheme, which employs the minorization-maximization (MM) method. However, while centralized beamforming designs offer superior performance, they suffer from high computational complexity, substantial communication overhead, and demand expensive computational resources. To surmount these challenges, we present a framework that facilitates per-link parallel and distributed HYBF (P&D- HYBF) in the mmWave frequency band. This cooperative approach enables each base station (BS) to independently solve its local, low-complexity sub-problems in parallel, resulting in a substantial reduction in communication overhead and computational complexity. Simulation results demonstrate that P&D-HYBF achieves comparable performance to C-HYBF, and with only a few radio-frequency (RF) chains, both designs surpass the capabilities of fully digital half duplex (HD) systems.

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Hybrid Beamforming and Combining for Millimeter Wave Full Duplex Massive MIMO Interference Channel

Full Duplex (FD) communication can revolutionize wireless communications as it avoids using independent channels for bi-directional communications. This work generalizes the point-to-point FD communication in millimeter wave (mmWave) band consisting of K-pairs of massive MIMO FD nodes operating simultaneously. We present a novel joint hybrid beamforming (HYBF) and combining scheme for weighted sum-rate (WSR) maximization to enable the coexistence of massive MIMO FD links cost-efficiently. The proposed algorithm relies on alternative optimization based on the minorization-maximization method. Moreover, we present a novel SI and massive MIMO interference channel aware power allocation scheme to include the optimal power control. Simulation results show significant performance improvement compared to a traditional bidirectional fully digital half-duplex (HD) system.

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Practical Hybrid Beamforming for Millimeter Wave Massive MIMO Full Duplex with Limited Dynamic Range

Full Duplex (FD) radio has emerged as a promising solution to increase the data rates by up to a factor of two via simultaneous transmission and reception in the same frequency band. This paper studies a novel hybrid beamforming (HYBF) design to maximize the weighted sum-rate (WSR) in a single-cell millimeter wave (mmWave) massive multiple-input-multiple-output (mMIMO) FD system. Motivated by practical considerations, we assume that the multi-antenna users and hybrid FD base station (BS) suffer from the limited dynamic range (LDR) noise due to non-ideal hardware and an impairment aware HYBF approach is adopted by integrating the traditional LDR noise model in the mmWave band. In contrast to the conventional HYBF schemes, our design also considers the joint sum-power and the practical per-antenna power constraints. A novel interference, self-interference (SI) and LDR noise aware optimal power allocation scheme for the uplink (UL) users and FD BS is also presented to satisfy the joint constraints. The maximum achievable gain of a multi-user mmWave FD system over a fully digital half duplex (HD) system with different LDR noise levels and numbers of the radio-frequency (RF) chains is investigated. Simulation results show that our design outperforms the HD system with only a few RF chains at any LDR noise level. The advantage of having amplitude control at the analog stage is also examined, and additional gain for the mmWave FD system becomes evident when the number of RF chains at the hybrid FD BS is small.

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Game-Theoretic Mode Scheduling for Dynamic TDD in 5G Systems

Dynamic time-division duplexing (TDD) enables independent uplink/downlink mode scheduling at each cell, based on the local traffic. However, this creates cross-interference among cells. Thus, the joint power allocation and scheduling problem becomes mixed-integer non-convex and turns out to be NP-hard. We propose a low-complexity and decentralized solution, where power allocation and scheduling are decoupled. First, power is allocated in a decentralized fashion, and then modes are scheduled by a non-cooperative game to achieve the mixed-strategy Nash equilibrium. We consider two possible approaches to compute the payoffs in the game, according to the cross-interference power model and the entailed communication overhead among cells. Simulation results are presented for an outdoor dense small-cell scenario, showing that our approaches outperform static TDD significantly.

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