No abstract

No abstract

In an 802.11ac-based MU-MIMO network comprised of multiple cells 1 , inter-cell interference allows only a single AP to serve its clients at the same time, significantly limiting the network capacity. In this work, we overcome this limitation by letting the APs and clients in interfering cells coordinately cancel the inter-cell interference using their antennas for beamforming. To achieve such coordinated interference cancellation in a practical way, we propose a novel two-step optimization. First, without requiring any channel knowledge, each AP and client optimizes the use of its antennas for either data communication or inter-cell interference cancellation, in order to maximize the total number of deliverable streams in the MU-MIMO network. Second, with only partial channel knowledge, each AP and client optimizes their beamforming weights after the optimal antenna usage has been identified in the first step. Our solution, CoaCa, integrates this two-step optimization into 802.11ac with small modifications and negligible overhead, allowing each AP and client to locally perform the two-step optimization. Our experimental evaluation indicates that for a MU-MIMO network with two cells, by cancelling the inter-cell interference CoaCa can convert the majority of the expected number of streams increase (50%-67%) into network capacity improvement (41%-52%).

This paper investigates the application in IEEE 802.11ac/ax systems of the received bit information rate (RBIR) technique in order to estimate the effective signal-tointerference-plus-noise ratio used to abstract the physical layer (PHY) performance in system level simulations. The RBIR technique is evaluated based on simulation results of IEEE 802.11ac PHY operating over canonical flat fading and spatial-correlated frequency selective single-user and multiuser multiple input multiple output channels. We have concluded that the RBIR PHY abstraction methodology is accurate enough to provide first order insights on system level performance and design options with reduced computational complexity. Finally, the application of RBIR PHY abstraction scheme to schedule the modulation and code schemes on the flight to achieve a target quality-ofservice is also described.

No abstract