Cognitive coexistence: A throughput study of MUD-enhanced opportunistic spectrum access

Abstract

A new opportunistic spectrum access overlay/underlay paradigm for enabling heterogeneous wireless networks of primary and secondary, or multiple "secondary" users to coexist on the same frequency in the same geographic location is proposed and evaluated. In this new paradigm of cognitive coexistence, underlay nodes operate without overt coordination with overlay nodes or other underlay bases. Instead of overt coordination, the underlay nodes monitor their local environment and their effect upon it to determine acceptable channels for coexistence. Moreover, with the employment of multiuser detection in some or all of the underlay nodes (and in none of the overlay nodes), high rate underlay links are possible in the presence of even the most severe overlay interference. The result is a backward compatible coexistence of overlay and underlay nodes with high throughput for the underlay network while maintaining acceptable data rates for the overlay network. This paper describes what we define as the cognitive coexistence strategy (CCS) that enables nodes to determine among all occupied bands which band is most likely to result in a successful coexistence between its link and the already existing link on that band. The CCS takes advantage of the adaptive nature of the overlay nodes and the unpredictable, but often present asymmetric channel due to the different path losses between a transmitter and its intended and unintended receivers. This paper presents a preliminary simulation-based investigation of the opportunity that exists for a pair of cognitive coexistence radios (CCR) operating as a small cell base and mobile in an urban wireless cellular environment, showing sufficient opportunity for high throughput coexistence that can be advantaged by the cognitive capability of the CCR nodes.

A MUD/rate selection tool for cognitive radios in packet based asynchronous Gaussian multiple access channels

“…If the first occupants of the channel form a traditional non-rate-adaptive network, it is incumbent on the infringing nodes to guarantee the current level of service for the existing nodes; this "do no harm" problem well matched to the coexistence system proposed in [3]. On the other hand, should the traditional network be rate adaptive, a "do no harm" rule is no longer imperative for all users to enjoy successful communication in an ad hoc IMA environment; this is the new paradigm enabled by the cognitive coexistence radio and strategy proposed in [1], [2], [4].…”

“…where Q is obtained by Cholesky factorization of Π, Y w = Q H Y and A, b are as in (2). N w now has covariance σ 2 n I.…”

“…For the minimum exposure approach to coexistence, this tool would be relied upon to set the MUD and rate choices for the cognitive radio pair. For the approach of "do no significant harm" the accommodation of a suitable rate for the established traditional node is addressed by the cognitive coexistence radio (CCR) of [2], [4]. This paper develops a tool that would be used by the CCR to create possible options for consideration, probing, and testing, to enable the CCR pair to settle into a successful coexistence.…”

“…Our main concern in this work lies in providing and demonstrating these technologies when taken in tandem and applied to the interference multiple access (IMA) paradigm such as the coexistence systems proposed in [1], [2] and [3]. IMA is a general concept wherein cochannel interference tolerant nodes are either assigned, or select on their own, a communications frequency band already assigned to another node or expected to contain a packet transmission from another node.…”

Resource sharing in heterogeneous cloud radio access networks

“…Resource sharing has been extensively investigated in terms of spectrum sharing [9,11], infrastructure sharing [7,10], and network sharing [12,13]. In such investigations, research focused on topics such as resource scheduling, fairness, reliability, flexibility, elasticity, energy efficiency, CAPEX and OPEX minimization, and interference management.…”