Spectrum clouds: A session based spectrum trading system for multi-hop cognitive radio networks

Abstract

Abstract-Spectrum trading creates more accessing opportunities for secondary users (SUs) and economically benefits the primary users (PUs). However, it is challenging to implement spectrum trading in multi-hop cognitive radio networks (CRNs) due to harsh cognitive radio (CR) requirements on SUs' devices and complex conflict and competition relationship among different CR sessions. Unlike the per-user based spectrum trading designs in previous studies, in this paper, we propose a novel session based spectrum trading system, spectrum clouds, in multihop CRNs. In spectrum clouds, we introduce a new service provider, called secondary service provider (SSP), to harvest the available spectrum bands and facilitate the accessing of SUs without CR capability. The SSP also conducts spectrum trading among CR sessions w.r.t. their conflicts and competitions. Leveraging a 3-dimensional (3-D) conflict graph, we mathematically describe the conflicts and competitions among the candidate sessions for spectrum trading. Given the rate requirements and bidding values of candidate trading sessions, we formulate the optimal spectrum trading into the SSP's revenue maximization problem under multiple cross-layer constraints in multi-hop CRNs. In view of the NP-hardness of the problem, we have also developed heuristic algorithms to pursue feasible solutions. Through extensive simulations, we show that the solutions found by the proposed algorithms are close to the optimal one.

Optimizing Spectrum Sharing in Wireless Mesh Network Using Cognitive Technology

“…A novel spectrum trading system is proposed in [33] and a theoretical study on the optimal session based spectrum trading problem is presented under multiple cross-layer constraints in multi-hop CRs. A general secondary spectrum trading framework is presented in [25].…”

Spectrum-aware data replication in intermittently connected cognitive radio networks

“…Constraint (2) ensures that each node replicates at most S coded packets for each data item since a data item can be reconstructed by any S packets of it. Constraint (3) ensures that the total number of packets replicated by each node does not exceed the storage space of that node.…”

“…Depending on the network architecture, cognitive radio networks can be either infrastructure-based or ad-hoc based, where cognitive radio ad-hoc networks [2], [3], [4], [5] do not require any infrastructure support. They allow unlicensed users to detect available licensed channels and then establish connections by themselves.…”

A novel protocol for transparent and simultaneous spectrum access between the secondary user and the primary user in cognitive radio networks

“…3 This has been motivated by the well documented under-utilization 4 of licensed spectrum and the growing interest in exploiting "white 5 spaces" or unused spectrum. Research on the SU spectrum access can 6 be categorized either as geo-location based spectrum access [2-7], or 7 opportunistic spectrum access [8][9][10][11][12][12][13][14]. Geo-location based spec-8 trum access relies on primary users (PUs) exhibiting spatially and/or 9 temporally predictable behavior.…”

“…Geo-location based spec-8 trum access relies on primary users (PUs) exhibiting spatially and/or 9 temporally predictable behavior. If PU behavior does not exhibit pre- 10 dictability, then spectrum sharing often falls into opportunistic spec- 11 trum access, where secondary users (SUs) perform spectrum sensing 12 to dynamically detect PU channel access, and opportunistically 13 access the channel during the period between two PU transmissions. 14 Recently there has been significant interest on medium access con- 15 trol (MAC) protocols for CRNs.…”