Hoiyoon Jung

Cooperative Spectrum Sensing for IEEE 802.22 WRAN System

In this paper, we propose two novel data fusion schemes for cooperative spectrum sensing in the IEEE 802.22 WRAN system. The data fusion structure is proper for the WRAN system due to its centralized structure, and it can provide reliable sensing performance. The proposed data fusion schemes improve the sensing reliability by utilizing confidence vector of the sensing result. Moreover, application with statistic weight on the confidence vector provides additional performance gain. The computer simulation results show that the proposed data fusion methods guarantee better sensing performance than the conventional data fusion algorithms.

Cognitive Radio test-bed based on ECMA-392 International Standard

Cognitive Radio (CR) technology is one of the promising technology to efficiently utilize the unused radio spectrum. Recently, the Federal Communications Commission (FCC) allowed TV white space (TVWS) to be used for data communications provided the licensed user operations should be protected. The FCC made the rules and regulation for using the TVWS. Till now there is no real deployment of any communication system that operates on TVWS. As the first step towards the deployment of a communication system that operates on TVWS, we developed a UHF band CR test-bed based on ECMA-392 international standard. ECMA-392 standard defines the MAC and PHY for operation in TVWS for communication between portable devices. In this paper, we present the design and implementation of our test-bed system in detail. We also verified that the test-bed system operates in lines with the FCC rules.

Throughput Performance Optimization of Super Dense Wireless Networks With the Renewal Access Protocol

As a promising solution for handling super dense wireless networks, wireless local area networks (WLANs) have been intensively considered due to their wide availability. However, the contention-based MAC protocol in WLANs should be modified because of its inefficiency. To this end, we consider a recently proposed novel MAC protocol called the renewal access protocol (RAP). With the RAP, we analyze two strategies for resolving collisions efficiently and achieving optimal throughput performance in super dense WLANs: strategies without and with grouping. First, we analyze the asymptotic behavior of the RAP itself (i.e., without grouping) as the number of terminals goes to infinity. We show that the RAP can achieve optimal throughput even in super dense WLANs and the relevant optimal access probability can be derived in a closed form. Second, we propose a grouping strategy in the RAP called the grouped RAP (G-RAP). While a grouping strategy in the IEEE 802.11ah standard is based on time division, our G-RAP is based on transmission attempts. So the G-RAP does not waste channel resources. We show that the G-RAP achieves the optimal network throughput for any group structure if terminals use the optimal access probability that we derive. Our analytical results are validated by simulation.

Efficient multi-channel signal detection algorithms for cognitive radio systems in TV white space

In this paper, we propose novel spectrum sensing algorithms to detect multi-channel CR signal in TV white space. Most of CR systems in TV white space are considering multi-channel operation to support enhanced system throughput. Therefore, spectrum sensing algorithm to detect multi-channel CR system is essentially required for coexistence in TV white space. The proposed algorithms can detect various types of multi-channel CR signal with reasonable detection performance. By employing the proposed algorithms, we can contribute to efficient implementation of spectrum sensing process as well as intelligent coexistence mechanisms in TV white space.

Novel CR signal detection algorithms for coexistence in TV white space

In this paper, we propose novel signal detection algorithms for coexistence of CR systems in TV white space. As various CR standards appear in TV white space, technologies for detecting CR signals are required to enabling coexistence between CR systems. The proposed signal detection algorithms detect and classify CR networks utilizing cyclo-stationary features of each CR system. They consider multiple periodic properties of OFDM signal which is varied by parameters of each CR standard. The simulation results show that the proposed schemes can improve signal detection performance up to 50% compare with the conventional schemes.

Optimal throughput analysis of a super dense wireless network with the Renewal Access Protocol

As Wireless Local Area Networks (WLANs) become denser and denser recently, the contention-based MAC protocol such as the IEEE 802.11 DCF, the de facto standard for the WLAN, should be modified to handle such dense WLANs. To this end, we consider a recently proposed novel MAC protocol called the Renewal Access Protocol (RAP) in this paper. With the RAP, we consider two strategies for resolving collisions efficiently and achieving high throughput performance in a super dense WLAN: strategies without and with grouping. First, we analyze the asymptotic behavior of the RAP itself (i.e., without grouping) as the number of terminals goes to infinity. We show that the RAP can achieve optimal throughput even in a super dense WLAN and the related optimal access probability of the RAP can be derived in a closed-form from the analysis. Second, we propose a new grouping strategy in the RAP and call it the grouped RAP (G-RAP). While a grouping strategy in the IEEE 802.11ah standard is based on time division, which can cause a waste of channel, our grouping strategy is based on transmission attempts, which does not waste channel resources. From the analysis we show that the G-RAP easily achieves the optimal network throughput performance for any group structure (i.e., unform group size and arbitrary group size) if terminals use the optimal access probability that we derive. Our analytical results are validated by simulation.

Development and performance improvement of cognitive radio testbed on TV white space

Cognitive radio technologies have been studied for enhancing various aspects of wireless communication in terms of optimization of system parameters or dynamic spectrum access. Recently, testbed implementations have been frequently introduced to verify the feasibilities of these researches. The possibility on sharing TV bands with an unlicensed service is also proved by several platforms for data communication using TV white space. In this paper, we introduce a cognitive radio testbed which can improve the system capacity by using carrier aggregation functionality or 2×2 MIMO on the UHF TV bands. Detailed design and implementation issues focused on carrier aggregation are described. Finally, operating scenario and performance evaluation of our testbed are demonstrated.

Advanced cognitive radio test-bed with carrier aggregation in TV white space

Cognitive radio (CR) has been getting attention as a remarkable technology to improve spectrum efficiency by utilizing unused spectrum resources. Especially, many countries have been considering permission for CR-based spectrum usage of TV white space (TVWS). Even though TV band has favorable propagation property compared to other higher frequency bands, CR system in TVWS involves a fundamental limit on system capacity because of a restricted TV channel bandwidth. To overcome it, in this paper, we introduce new CR test-bed with capability of carrier aggregation. By utilizing carrier aggregation functionality, we can effectively utilize multiple TV channels and achieve higher system capacity. Moreover, the test-bed supports non-contiguous carrier aggregation as well as contiguous carrier aggregation. Because unused TV channels are spread over entire TV band sporadically in general, new test-bed provides noticeable performance improvement compared to the existing CR systems in TVWS. Detailed implementation of the test-bed including each functional module is explained, and functional test procedures with corresponding results are provided for evaluation.

Novel incremental spectrum sensing method based on sequential tone detection

In this paper, we propose a novel incremental spectrum sensing method based on sequential tone detection. The conventional spectrum sensing algorithm using FFT computes all frequency components in a process, thus it requires unnecessary complexity. To overcome this drawback, sequential spectrum sensing algorithm utilizing DFT was proposed, and it shows almost same detection performance with reduced complexity. The proposed method of this paper utilizes Goertzel algorithm, and it provides improved signal detection performance with further reduced computational complexity compare with the conventional schemes. The simulation results verify that it provides 10% enhancement on detection probability with significantly reduced system complexity.

Efficient spectrum sensing algorithm utilizing sequential partial band search

In this paper, we propose an efficient spectrum sensing algorithm utilizing sequential partial band search. The conventional sensing algorithm using FFT contains redundant computation due to the characteristic of FFT which computes all frequency components at one time. The proposed sensing algorithm utilizing DFT computes a frequency component once at a time according to the priority and decides presence of signal. The proposed sensing algorithm can provide similar detection performance to the conventional scheme while computations of the sensing process could be reduced significantly depends on an early detection of signal.