In dynamic spectrum access (DSA), secondary users (SU) should only be allowed to access a licensed band belonging to incumbent users (IU) when the quality-of-service (QoS) requirements of both IUs and SUs can be satisfied at the same time. However, IU’s location and its received interference strength are considered sensitive in many DSA systems which should not be revealed, making it very challenging to optimize the network utility subjected to satisfying the operation and security requirements of SUs and IUs. In this paper, we develop a secure and distributed SU transmit power control algorithm to solve this challenge. Our algorithm achieves optimal SU power control to maximize the sum of SU rates. The SINR-guaranteed coexistence between SUs and IUs are enabled to maintain effective communication, while no information is directly required from IUs. Local measurements of IU signals provided by Environmental sensing capability (ESC) also undergo a security masking process to ensure that IU location cannot be derived from its outputs. Convergence and stability properties of our algorithm and its privacy-protection strength are both theoretically analyzed and experimentally evaluated through simulations
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Cross-Layer Band Selection and Routing Design for Diverse Band-Aware DSA Networks
As several new spectrum bands are opening up for shared use, a new paradigm of Diverse Band-aware Dynamic Spectrum Access (d-DSA) has emerged. d-DSA equips a secondary device with software defined radios (SDRs) and utilize whitespaces (or idle channels) in multiple bands, including but not limited to TV, LTE, Citizen Broadband Radio Service (CBRS), unlicensed ISM. In this paper, we propose a decentralized, online multi-agent reinforcement learning based cross-layer BAnd selection and Routing Design (BARD) for such d-DSA networks. BARD not only harnesses whitespaces in multiple spectrum bands, but also accounts for unique electro-magnetic characteristics of those bands to maximize the desired quality of service (QoS) requirements of heterogeneous message packets; while also ensuring no harmful interference to the primary users in the utilized band. Our extensive experiments demonstrate that BARD outperforms the baseline dDSAaR algorithm in terms of message delivery ratio, however, at a relatively higher network latency, for varying number of primary and secondary users. Furthermore, BARD greatly outperforms its single-band DSA variants in terms of both the metrics in all considered scenarios.
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- Award ID(s):
- 1642873
- NSF-PAR ID:
- 10314989
- Date Published:
- Journal Name:
- GLOBECOM 2020 - 2020 IEEE Global Communications Conference, 2020
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract—The mainstay of current spectrum access grants exclusive rights to proprietary occupants who exhibit tidal traffic patterns, leading to low usage of valuable spectrum resources. To remedy this situation, Dynamic Spectrum Access (DSA) is proposed to allow Secondary Users (SUs) to opportunistically exploit idle spectrum slices left by Primary Users (PUs). The key to the success of DSA lies in SUs’ knowledge on radio activities of PUs. To enhance the understanding of PU spectrum tenancy patterns, various mathematical models have been proposed to describe spectrum occupancy dynamics. However, there are still two overlooked aspects in existing studies on spectrum tenancy modeling, i.e., time-varying spectrum tenancy patterns and multi- ple channels within the same Radio Access Technology (RAT). To address the two issues, we apply a change detection algorithm to discover time points where spectrum tenancy patterns vary, and propose to characterize spectrum usage in a multi-channel RAT by the Vector Autoregressive (VAR) model. Through analyzing LTE spectrum tenancy data with the algorithm and the model, we validate that the segment size discovered by the online change detection method coincides with the one obtained by brute force, and VAR outperforms the widely adopted on/off model.more » « less
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null (Ed.)In this letter, we investigate the idea of interference spreading and its effect on bit error rate (BER) performance in a cognitive radio network (CRN). The interference spreading phenomenon is caused because of the random allocation of subcarriers in an orthogonal frequency division multiplexing (OFDM)-based CRN without any spectrum-sensing mechanism. The CRN assumed in this work is of underlay configuration, where the frequency bands are accessed concurrently by both primary users (PUs) and secondary users (SUs). With random allocation, subcarrier collisions occur among the carriers of primary users (PUs) and secondary users (SUs), leading to interference among subcarriers. This interference caused by subcarrier collisions spreads out across multiple subcarriers of PUs rather than on an individual PU, therefore avoiding high BER for an individual PU. Theoretical and simulated signal to interference and noise ratio (SINR) for collision and no-collision cases are validated for M-quadrature amplitude modulation (M-QAM) techniques. Similarly, theoretical BER performance expressions are found and compared for M-QAM modulation orders under Rayleigh fading channel conditions. The BER for different modulation orders of M-QAM are compared and the relationship of average BER with interference temperature is also explored further.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/GLOBECOM42002.2020.9322500
