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1. Mitigation of the spectrum sensing data falsifying attack in cognitive radio networks

   https://doi.org/10.1080/23335777.2020.1811387  

   Biswas, Rajorshi ; Wu, Jie ; Du, Xiaojiang ; Yang, Yaling ( September 2020 , Cyber-Physical Systems)

   Cognitive radio networks (CRNs), which offer novel network architecture for utilising spectrums, have attracted significant attention in recent years. CRN users use spectrums opportunistically, which means they sense a channel, and if it is free, they start transmitting in that channel. In cooperative spectrum sensing, a secondary user (SU) decides about the presence of the primary user (PU) based on information from other SUs. Malicious SUs (MSUs) send false sensing information to other SUs so that they make wrong decisions about the spectrum status. As a result, an SU may transmit during the presence of the PU or may keep starving for the spectrum. In this paper, we propose a reputation-based mechanism which can minimise the effects of MSUs on decision making in cooperative spectrum sensing. Some of the SUs are selected as distributed fusion centres (DFCs), that are responsible for making decisions about the presence of PU and informing the reporting SUs. A DFC uses weighted majority voting among the reporting SUs, where weights are normalised reputation. The DFC updates reputations of SUs based on confidence of an election. If the majority wins by a significant margin, the confidence of the election is high. In this case, SUs that belong to the majority gain high reputations. We conduct extensive simulations to validate our proposed model. 

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2. Change Detection Based Segmentation and Modeling of LTE Spectrum Tenancy

   https://doi.org/10.1109/GLOBECOM38437.2019.9013749  

   Zou, Rui ; Wang, Wenye ( December 2019 , IEEE GLOBECOM)

   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. 

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3. Massive MIMO Cognitive Cooperative Relaying

   https://doi.org/10.1007/978-3-030-23597-0_8  

   Dinh, S. ; Liu, H. ; Ouyang, F. ( June 2019 , Springer LNCS Wireless Algorithms, Systems, and Applications)

   This paper proposes a novel cognitive cooperative transmission scheme by exploiting massive multiple-input multiple-output (MMIMO) and non-orthogonal multiple access (NOMA) radio technologies, which enables a macrocell network and multiple cognitive small cells to cooperate in dynamic spectrum sharing. The macrocell network is assumed to own the spectrum band and be the primary network (PN), and the small cells act as the secondary networks (SNs). The secondary access points (SAPs) of the small cells can cooperatively relay the traffic for the primary users (PUs) in the macrocell network, while concurrently accessing the PUs’ spectrum to transmit their own data opportunistically through MMIMO and NOMA. Such cooperation creates a “win-win” situation: the throughput of PUs will be significantly increased with the help of SAP relays, and the SAPs are able to use the PU’s spectrum to serve their secondary users (SUs). The interplay of these advanced radio techniques is analyzed in a systematic manner, and a framework is proposed for the joint optimization of cooperative relay selection, NOMA and MMIMO transmit power allocation, and transmission scheduling. Further, to model network-wide cooperation and competition, a two-sided matching algorithm is designed to find the stable partnership between multiple SAPs and PUs. The evaluation results demonstrate that the proposed scheme achieves significant performance gains for both primary and secondary users, compared to the baselines. 

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4. Gaussian random field approximation for exclusion zones in cognitive radio networks

   https://doi.org/10.1109/PIMRC.2017.8292398  

   Wang, Zheng ; Mark, Brian L. ( October 2017 , IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC))

   To protect primary users from interference caused by secondary users (SUs) in a cognitive radio network, a geographic area called an exclusion zone can be defined in which SUs are prohibited from transmitting using a specified spectrum band. We propose a Gaussian Random Field Model (GRFM) framework for determining an exclusion zone with the desired properties in practical scenarios where analytical specifications may not be available. Based on the GRFM, we derive the radius of a disk determining the exclusion zone, assuming that the SUs are distributed geographically over a planar coverage area. Using measurement data obtained from SUs, the GRFM is applied to approximate the equivalent received signal power and aggregate interference at specified locations. Simulation results show that the GRFM approximation yields an accurate characterization of the exclusion zone. 

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5. Physics-inspired heuristics for soft MIMO detection in 5G new radio and beyond

   https://doi.org/10.1145/3447993.3448619  

   Kim, Minsung ; Mandrà, Salvatore ; Venturelli, Davide ; Jamieson, Kyle ( January 2021 , Proceedings of the 27th Annual International Conference on Mobile Computing and Networking)

   null (Ed.)

   Overcoming the conventional trade-off between throughput and bit error rate (BER) performance, versus computational complexity is a long-term challenge for uplink Multiple-Input Multiple-Output (MIMO) detection in base station design for the cellular 5G New Radio roadmap, as well as in next generation wireless local area networks. In this work, we present ParaMax, a MIMO detector architecture that for the first time brings to bear physics-inspired parallel tempering algorithmic techniques [28, 50, 67] on this class of problems. ParaMax can achieve near optimal maximum-likelihood (ML) throughput performance in the Large MIMO regime, Massive MIMO systems where the base station has additional RF chains, to approach the number of base station antennas, in order to support even more parallel spatial streams. ParaMax is able to achieve a near ML-BER performance up to 160 × 160 and 80 × 80 Large MIMO for low-order modulations such as BPSK and QPSK, respectively, only requiring less than tens of processing elements. With respect to Massive MIMO systems, in 12 × 24 MIMO with 16-QAM at SNR 16 dB, ParaMax achieves 330 Mbits/s near-optimal system throughput with 4--8 processing elements per subcarrier, which is approximately 1.4× throughput than linear detector-based Massive MIMO systems. 

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