QoS-Aware Power Allocations for Maximizing Effective Capacity Over Virtual-MIMO Wireless Networks

Abstract

Abstract-To enable multiple mobile users to transmit their signals simultaneously over the same sub-channels, the virtual multiple-input multiple-output (V-MIMO) techniques can exploit the multiple-input multiple-output (MIMO) spectrum efficiency gain. Traditional V-MIMO transmission schemes mainly focus on maximizing the throughput of grouped mobile users without taking into account the quality-of-service (QoS) provisionings. In this paper, we propose the optimal power allocation schemes with statistical QoS provisionings to maximize the effective capacity of non-collaborative/collaborative V-MIMO wireless networks, respectively. For non-collaborative V-MIMO wireless networks, the mobile users in one V-MIMO group transmit signals independently over the same sub-channels. In the view point of existing mobile users, they solely occupy the sub-channels. Thus, the existing mobile users employ the QoS-driven single-user power allocation scheme to maximize their effective capacity. By converting the non-collaborative V-MIMO transmission optimization problem into a strictly convex optimization problem, we derive the QoS-driven power allocation scheme for the newly added mobile users to maximize their effective capacity. For collaborative V-MIMO wireless networks where the mobile users in one group can collaboratively transmit their signals, we derive the QoS-driven collaborative power allocation schemes for both the existing and the newly added mobile users. Also conducted is a set of simulation evaluations, showing that our proposed power allocation schemes for V-MIMO wireless networks outperform the other existing schemes.

Achieving QoS in Virtual MIMO systems: a satisfaction equilibrium analysis

“…Traditional VMIMO transmission schemes principally focus on maximizing the throughput of grouped mobile terminals without taking into account the quality-of-service (QoS) provisioning. The authors in [12] propose the optimal power allocation schemes with statistical QoS provisioning to maximize the effective capacity of noncollaborative/collaborative VMIMO wireless networks, respectively. Xu Hongli et al study in [13] the problem of constructing an energy-efficient topology in wireless sensor networks using VMIMO communication.…”

A unified framework for adaptive inverse power control

“…Several adaptive inverse control methods have been developed and studied in the literature for power control, e.g., [14,15,[19][20][21][22][23][24]. The conventional 1-bit adaptive power control (CAPC-1) method [14,19] employs delta modulation, i.e., adjusts the previous transmission power up or down by a fixed step.…”

Resource allocation for statistical QoS guarantees in MIMO cellular networks

“…Guo et al [7] derives the effective capacity for MIMO channels under maximal ratio combining and adaptive modulation, by modeling a MIMO channel in terms of its number of DoFs as a Markov chain and conditioning on the number of DoFs, and [25] uses the effective capacity theory to perform optimal power allocation for a group of independent mobile stations in a virtual MIMO system in the uplink direction. In our problem, we consider multi-user MIMO in the downlink, where total available power is limited and we have a larger number of stations communicating as compared to the limit of two in [25]. Cheng et al [26] proposes power and spectrum efficiency indexes considering point-to-point MIMO links using effective capacity.…”

“…The authors of [39] consider a virtual MIMO uplink system, where power allocation is optimally performed among existing and new users, such that the effective capacity of existing users is satisfied, while the new users get the maximum possible effective capacity. In that work, successive interference cancellation is performed but no specific precoding technique is employed, unlike superposition coding used in our work.…”