Kazunori Takeuchi

Predicting Radio Resource Availability in Cognitive Radio - an Experimental Examination

This paper presents a method for predicting radio resource availability in cognitive radio. In this paper, unlike a primary/secondary model, cognitive radio is defined as wireless communication technology in which each node communicates via an optimal wireless system based on recognition of radio resource availability in heterogeneous wireless communication systems. Therefore, it is important to be able to recognize such radio resource availability accurately. However, a cognitive radio node is unable to recognize the subsequent radio resource availability at the time of selecting the optimal wireless system. The authors focus on the prediction of radio resource availability to resolve the above issue. In this paper, the authors focus on IEEE802.11 and radio channel occupation time, which is calculated from packet length and the transmission rate, is used as radio resource availability. From the results of the examination, it would seem feasible that the auto-correlation coefficient (or partial auto-correlation coefficient) could be utilized as information on the reliability of the prediction value when an auto-regression model (AR model) is used for the prediction. Furthermore, by comparing n-step-ahead prediction for a time series calculated for a 1-second interval and 1-step-ahead prediction for a time series calculated for an n-second interval, it is shown that the accuracy of the prediction in both cases is almost identical when the information volume to calculate a prediction expression is the same. Therefore, either prediction approach can be selected depending on the cognitive radio system.

Packet Switch and Its Impact on Dynamic Base Station Relocation in Mesh Networks Using Cognitive Radio

CR (Cognitive Radio) is a technology that can realize more intensive and efficient spectrum use through spatial and temporal utilization. In the context of mesh networks where each base station consists of heterogeneous multi-radio interfaces, packet switch in L2/L3 of each base station selects each radio interface and channel adaptively in order to take full advantage of all multiple heterogeneous interfaces. At first, this paper examines the achievable performance of the new packet switch schemes in mesh topology. Secondly, we investigate the potentiality of dynamic base station relocation approach in order to cope with the change of terminal traffic distribution, and show the impact of packet switch policy on dynamic base station relocation.

A Study on Rotational OFDM Transmission with Multi-Dimensional Demodulator and Twin Turbo Decoder

This paper proposes rotational orthogonal frequency division multiplexing (R-OFDM) transmission with multi-dimensional demodulator (MDD) and twin turbo decoder (T2D). R-OFDM uses rotational multi-carrier modulation (R-MCM), which provides suitable frequency diversity gain in any coding rates although coded OFDM cannot obtain it in high coding rates. In addition, by applying MDD to its receiver, R-OFDM does not cause inter symbol interference degrading multi-carrier code division multiplexing (MC-CDM) with Walsh code multiplexing (WCM). Then, aiming at high spectrum efficiency, T2D is also proposed. T2D is based on a turbo decoder and has the proposed likelihood estimation taking into account the mutual information between multiplexed bits in the identical received symbol. Computer simulations verify that the proposed scheme improves the packet error rate (PER) performance of not only MC-CDM with WCM, but also OFDM, and the required Es/N0 of the OFDM obtaining a PER of 1% is improved by about 1.5 dB at the maximum.

Experimental Verification on the Prediction of the Trend in Radio Resource Availability in Cognitive Radio

This paper presents a prediction of the trend in radio resource availability in cognitive radio. In this paper, cognitive radio is defined as the wireless communication technology in which each node communicates via an optimal wireless system based on recognition of the radio resource availability in heterogeneous wireless communication systems. We focused on the prediction of the network allocation vector (NAV) value for radio resource availability in IEEE 802.11, which is one of the candidates for installation in a cognitive radio [1]. We verified the prediction of the future value of the trend in the NAV time series; based on an auto-regressive model (AR model) and using captured data within a real environment. Based on the results of the verification, we show that prediction based on the AR model with suitable parameters is applicable in comparison when the average of the last 10 samples is used as a predicted value and the case where prediction is not applied. Furthermore, it is possible to set up a long update interval for the regression coefficients.

Channel occupancy estimation method for Wireless LAN

Channel occupancy is key information to realize efficient operation of the wireless system. Channel occupancy can be defined as the time occupancy ratio in the case of Wireless LAN (WLAN). We propose a novel passive method to estimate the time occupancy ratio of WLAN. The proposed method produces greater improvement in estimation accuracy compared with that of conventional methods. In this paper, we introduce the definition of the time occupancy ratio as the utilization index of a WLAN radio resource. Then, details of the proposal are introduced. Finally, the excellent evaluation results executed on an experimental system are introduced even when many loss packets exist.

Research project concerning cooperative heterogenious radio networks for reliability improvements

In Japan, several new Research and Development (R & D) projects have been started, whose main purpose is to attain the efficient use of the restricted resources of frequency bands. This paper introduces the objective and outline of the project in which we have been engaged. The test-bed facility has been developed and their features, specifications and some experimental results are also described. Our project focuses on cooperative heterogeneous radio networks to improve the reliability in the radio communication link. The technology developed in the project is considered to be advanced network technology that includes the cognitive radio system being studied in many research organizations.

Topology Management and Route Establishment Method for Base Station Networks Using Cognitive Radio

Cognitive radio, which utilizes the radio frequency spectrum efficiently by recognizing radio resource availability, is an attractive technology for overcoming the shortage of radio frequency. From the perspective of networking, cognitive radio technologies are also useful since they allow flexible network construction. This paper proposes base station networks using cognitive radio technologies. In order to achieve efficient utilization of the radio frequency spectrum and flexible network construction, we also propose a topology management and route control method for our proposed base station network. Our method shares the status of the wireless links along with topology information and establishes routes by using this information. Through simulation, we evaluate that our method significantly improves the throughput by efficient utilization of the radio frequency spectrum. Moreover, we demonstrate that our method works well when the size of the network gets larger.

A study of consolidating OFDMA radio networks for downlink in cognitive radio system

Cognitive radio is a great candidate for creating a new fundamental network architecture improving the efficiency of frequency resource usage. In a heterogeneous network, a cognitive radio system composed with a multi-transmission link is required to select the optimized wireless access network to the terminal. To make the proper selection of a wireless access network to the terminal, the relative amount of radio resources in use for each network is an important parameter. We call this parameter the “occupation level” in this paper, which is one of the most useful parameters for the selection as well as the Received Signal Strength Indicator (RSSI). A wireless access network adopting an Orthogonal Frequency Division Multiple Access (OFDMA) scheme has a certain occupation level in its Up Link / Down Link (UL/DL) resource allocation. The UL/DL resource allocation is not easily accessible from equipment outside the base station; how to extract these data and utilize them is unresolved. In this paper, we propose a new scheme for extracting and utilizing the UL/DL resource allocation for the occupation level of the cognitive radio in a Long Term Evolution (3GPP LTE) network. From the system load point of view, we confirmed the method is practical by examining these data being extracted from an LTE radio system while transmitting full buffered payload data.

Dynamic Base Station Relocation in Cognitive Mesh Networks Using Packet Switch

Cognitive radio is known as the technology that can make possible more intensive and efficient spectrum use through spatial and temporal utilization. In cognitive mesh networks where each base station consists of heterogeneous multi-radio interfaces, packet switch in L2/L3 of each base station selects each radio interface and channel adaptively in order to take full advantage of all multiple heterogeneous interfaces. In the context of cognitive mesh networks using packet switch, we investigate the potential of dynamic base station relocation problem in order to cope with the change of terminal traffic distribution, and show the impact of packet switch policies (i.e. interference based case, and channel non-usage ratio case) on dynamic base station relocation. Simulation result shows that our proposed dynamic base station relocation scheme is effective to increase the throughput performance, and that compared with the throughput performance of interference based case, the throughput of channel non-usage ratio case is always better. In addition we simulate the impact of pause time of client terminal movement model, and show that, with the increase of pause time, the throughput performance decreases.