Delay-Constrained Beamforming and Resource Allocation in Full Duplex Systems

Abstract

This paper studies the beamforming and resource allocation problem in a multiuser full duplex (FD) system with delay-awareness. We design a power-efficient algorithm to minimize the long-term sum transmit power under delay constraints. We do this by jointly optimizing the uplink transmit power and the downlink beamforming vectors while satisfying the long-term stability constraints on the queue buffers for the downlink and uplink users as well as quality of service constraints. Due to the stochastic nature of the problem, we exploit the classic drift-pluspenalty function and subsequently simplify the problem into a difference of convex functions. Building upon the transformed problem, we propose two algorithm designs, one, that exploits the users with good channel conditions for efficient resource allocation, and the other that ensures delay-fairness among all users based on the max-min formulation. Simulation results show significant gains achieved by the proposed FD schemes compared with the baseline HD schemes.

Uplink transmission with multiuser scheduling in non‐stand‐alone cellular network using virtual MIMO system

“…In recent times, resource allocation in uplink is part of extensive research due to less exposure. In Reference 8, the author has presented a max‐min and delay‐fairness algorithm for efficient resource allocation among UEs under good channel conditions. In Reference 9, the author has introduced a 5GNR physical layer framework.…”

Resource Allocation in Millimeter-Wave Multicarrier-Division Duplex Systems With Hybrid Beamforming

“…Moreover, the authors of [18] developed an optimal iterative RA algorithm, aiming at minimizing the total power consumption via jointly optimizing DL beamformer, UL transmit power and antenna selection. In [19], the authors jointly optimized the UL transmit power and DL beamforming to minimize the long-term transmit power under delay constraints. Although all the above-mentioned works endeavor to exploit the resources provided by FD, the SI problem, which is regarded as the biggest obstacle to achieve high-efficiency FD communications, has not been assumed in a practical way.…”

“…More specifically, the SI was directly assumed as Gaussian noise in [16], while in [17], SI was treated as a coefficient in the range of 70 dB to 110 dB. In [18] and [19], SI was assumed to be perfectly mitigated by a separate SIC subsystem before the beamforming design. To the authors' best knowledge, all the existing studies on the RA optimization in FD systems ignore the practical implementation of SIC, but assume a near-optimal SIC.…”

“…2) Direct Approach: Although the PGD algorithm with a decreasing step size guarantees the convergence to a local minimum, the difference between f f f d ZF [m] and F F F RF f f f d [m] may be increased by RA, especially when the number of RF chains is small, which results in that the interference in (19) from other MSs cannot be approximated to zero. In this case, Algorithm 2 may be hard to achieve the proportional rates among DL MSs at a sufficient accuracy, as the result that H m,d in (20) also includes p m,i , i ̸ = d, in addition to the desired p m,d .…”

Multiuser Scheduling In 3GPP LTE-A Uplink Non-Stand-Alone Cellular Network With Virtual MIMO

“…In recent times, resource allocation in uplink is a part of extensive research due to less exposure in past literatures. The efficient allocation of resources among the UEs under good channel conditions with a max-min and delay-fairness algorithm was presented in [8]. In [9], author introduced a 5G NR physical layer framework.…”