Convex approximation techniques for joint multiuser downlink beamforming and admission control

Abstract

Abstract-Multiuser downlink beamforming under quality of service (QoS) constraints has attracted considerable interest in recent years, because it is particularly appealing from a network operator's perspective (e.g., UMTS, 802.16e). When there are many co-channel users and/or the service constraints are stringent, the problem becomes infeasible and some form of admission control is necessary. We advocate a cross-layer approach to joint multiuser transmit beamforming and admission control, aiming to maximize the number of users that can be served at their desired QoS. It is shown that the core problem is NP-hard, yet amenable to convex approximation tools. Two computationally efficient convex approximation algorithms are proposed: one is based on semidefinite relaxation of an equivalent problem reformulation; the other takes a penalized second-order cone approach. Their performance is assessed in a range of experiments, using both simulated and measured channel data. In all experiments considered, the proposed algorithms work remarkably well in terms of the attained performance-complexity trade-off, consistently exhibiting close to optimal performance at an affordable computational complexity.

Joint Power and Admission Control for Ad-Hoc and Cognitive Underlay Networks: Convex Approximation and Distributed Implementation

“…In fact, if there are multiple solutions to (1)-(4), solving (15)-(18) will yield one of minimum sum power. The proof is by contradiction, similar to the line of argument in [19]. We skip it here for space considerations.…”

“…This is in the spirit of the approach in [19], albeit it does not follow as a special case. Let us consider the following problem:…”

“…To see this, pick = = = = 1, ∀ , 0 = 0 = 0 (no primary user), as in (19), as in (20), and link gains as in the proof of Claim 1. Let be an independent set of Γ.…”

“…Link gains are calculated by = 1/ 4 where is the Euclidean distance between transmitter and receiver , and receiver noise is set to −60 dBm. For our relaxation-based algorithms, the are kept close to the respective bounds (specifically at 0.999 times the value given by (20)) and is set to one order of magnitude smaller than the upper bound given by (19).…”

Joint bandwidth and power allocation in wireless multi-user decode-and-forward relay networks

“…The admission control in wireless networks typically aims at maximizing the number of admitted users and has been recently considered in several works. A singlestage reformulation approach for a two-stage joint resource allocation and admission control problem is proposed in [34], [35], while another approach is based on user removals [1], [3], [13], [14], [36]. To the best of our knowledge, admission control based on joint bandwidth and power allocation has never been considered.…”