Dynamic Cooperative Secondary Access in Hierarchical Spectrum Sharing Networks

Abstract

Abstract-We consider a hierarchical spectrum sharing network consisting of a primary and a cognitive secondary transmitter-receiver pair, with non-backlogged traffic. The secondary transmitter may utilize cooperative transmission techniques to relay primary traffic while superimposing its own information, or transmit opportunistically when the primary user is idle. The secondary user meets a dilemma in this scenario. Choosing cooperation it can transmit a packet immediately even if the primary queue is not empty, but it has to bear the additional cost of relaying, since the primary performance needs to be guaranteed. To solve this dilemma we propose dynamic cooperative secondary access control that takes the state of the spectrum sharing network into account. We formulate the problem as a Markov Decision Process (MDP) and prove the existence of a stationary policy that is average cost optimal. Then we consider the scenario when the traffic and link statistics are not known at the secondary user, and propose to find the optimal transmission strategy using reinforcement learning. With extensive numerical evaluation, we demonstrate that dynamic cooperation with state aware sequential decision is very efficient in spectrum sharing systems with stochastic traffic, and show that dynamic cooperation is necessary for the secondary system to be able to adapt to changing load conditions or to changing available energy resource. Our results show, that learning based access control, with or without known primary buffer state, has close to optimal performance. Index Terms-Hierarchical spectrum sharing, cooperative transmission, queuing systems, Markov decision process, reinforcement learning.

Stability and Dynamic Control of Underlay Mobile Edge Networks

“…In addition to above work, our results in this paper are also related to those on resource allocation and opportunistic scheduling for underlay cognitive radio networks (CRNs) [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]. The authors in [25] investigated the optimal power control and the resulting throughput scaling laws for underlay CRNs under average interference power constraints at the primary users.…”

“…In [31], the authors analyzed stable throughput for a primary multi-access system, where a secondary user (SU) receives packets from two primary users (PU) and relays them using the superposition coding technique when the primary slot is idle. The paper [32] studies the tradeoff between packet delay and energy consumption in a cooperative cognitive network. One common cooperation method is cooperative relaying [33].…”

Resource allocation for spectrum-leasing based CRN with delay-sensitive traffic

“…And with the help of the information theory, there has been extensive research on how to guarantee the benefits of spectrum-leasing based CRN via optimally allocate the wireless resources among PUs and SUs [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18], and a good summary of the state of the art is provided in [3,4]. Thereinto, the cooperation among PUs and SUs was commonly modeled by the convex optimization problem [5,6] where the globally optimal resource allocation is analytically derived, or by employing the widely used economical concepts, such as a Stackelberg game [2], a Nash Bargaining game [7][8][9], contract theory [10,11], auction theory [12,13], matching theory [14], etc.…”

“…Although some works [17,18] have been done for the delay-sensitive traffic, the delay metric is considered in the context of the deterministic delay guarantee, which is practically infeasible for wireless networks due to the time-varying nature of wireless channels. To address this issue, the statistical delay provisioning is adopted to ensure a small steady-state delay violation probability for the delay-sensitive traffic.…”

On Stable Throughput of Cognitive Radio Networks With Cooperating Secondary Users

“…In [14], authors analyzed stable throughput for a primary multi-access system where SU receives packets from two PUs and relays them using superposition coding technique when PU slot is idle. Fodor et al studied tradeoff between packet delay and energy consumption in a cooperative cognitive network [15]. A common cooperation method is cooperative relaying [16].…”