Spectrum Sensing Implemented with Improved Fluctuation-Based Dispersion Entropy and Machine Learning

Spectrum sensing is an important function in radio frequency spectrum management and cognitive radio networks. Spectrum sensing is used by one wireless system (e.g., a secondary user) to detect the presence of a wireless service with higher priority (e.g., a primary user) with which it has to coexist in the radio frequency spectrum. If the wireless signal is detected, the second user system releases the given frequency to maintain the principle of not interfering. This paper proposes a machine learning implementation of spectrum sensing using the entropy measure as a feature vector. In the training phase, the information about the activity of the wireless service with higher priority is gathered, and the model is formed. In the classification phase, the wireless system compares the current sensing report to the created model to calculate the posterior probability and classify the sensing report into either the presence or absence of wireless service with higher priority. This paper proposes the novel application of the FDE measure recently introduced in the research community as a feature vector to build the model and implement the classification. An improved implementation of the FDE (IFDE) is used to enhance the robustness to noise. IFDE is further enhanced with an adaptive method (AIFDE) to automatically select the hyper-parameter introduced in IFDE. Then, this paper combines the machine learning approach with the entropy measure approach, which are both recent developments in spectrum sensing research. The approach is compared to similar approaches in literature and the classical energy detection method using a generated radar signal data set with different conditions of SNR(dB) and fading conditions. The results show that the proposed approach is able to outperform the approaches from literature based on other entropy measures or the ED in a consistent way across different levels of SNR and fading conditions.

Development of Voice Call Transfer Service between Android Smart Phone and Tablet

Everyone necessitate communication technology in this information era. By use of modern technology, everyone should prefer wireless service without using bundle of wires. Colleges, shopping malls, corporate offices, coffee shops, construction buildings and restaurants provide Wi-Fi service to customers. Wi-Fi service allows data and voice transmissions over connected devices in same network. Proposed paper presents development of voice call transfer service that processes incoming telephone call which uses Wi-Fi as communication medium for voice transmission between smart phone and tablet. The proposed method allows real time communication transferred over wifi using IP between smart phone and tablet at no cost. Wi-Fi enabled smart phone and tablet are connected to the router or wifi access point to provide communication between caller and tablet user. Proposed paper develops cost effective, easy and reliable voice communication over Wi-Fi which provides good and comfort experience to user.

Electromagnetic Environment Portrait Based on Big Data Mining

With the development of IoT in smart cities, the electromagnetic environment (EME) in cities is becoming more and more complex. A full understanding of the characteristics of past spectrum resource utilization is the key to improving the efficiency of spectrum management. In order to explore the characteristics of spectrum utilization more comprehensively, this paper designs an EME portrait model. By checking the statistical information of the spectrum data, including changes in the noise floor and channel utilization in each individual wireless service, the correlation between the spectrum and time or space of different channels and the information is merged into a high-dimensional model through consistency transformation to form the EME portrait. The portrait model is not only convenient for storage and retrieval but also beneficial for transfer and expansion, which will become an important foundation for intelligent electromagnetic spectrum management.

Toward Spectral and Energy Efficient 5G Networks Using Relayed OFDM With Index Modulation

Next generation wireless networks are expected to provide much higher data throughput and reliable connections for a far larger number of wireless service subscribers and machine-type nodes, which results in increasingly stringent requirements of spectral efficiency (SE) and energy efficiency (EE). Orthogonal frequency-division multiplexing with index modulation (OFDM-IM) stands out as a promising solution to satisfy the SE requirement with a reasonable increase in system complexity. However, the EE of OFDM-IM is still required to be enhanced. Moreover, diversity gain is difficult to harvest from the frequency domain without affecting the SE for OFDM-IM systems, which hinders further reliability enhancement. In this regard, relay-assisted OFDM-IM, as a promising joint paradigm to achieve both high SE and EE, was proposed and has been studied since last year. The objectives of this study are to summarize the recent achievements of this joint paradigm, articulate its pros and cons, and reveal the corresponding challenges and future work. More importantly, we provide a full picture and insights into the implementation of this new paradigm in next generation networks.

The Value of Sharing Intermittent Spectrum

We examine a model of Cournot competition with congestion motivated by recent policy to allow commercial sharing of wireless spectrum that is assigned to other users such as government agencies. A key feature of such spectrum is that it is intermittently available because of the incumbent user’s activity. In our model, wireless service providers (SPs) compete for a common pool of customers using their own proprietary (exclusively licensed) bands of spectrum along with access to an additional intermittent band. When the intermittent band is unavailable, any traffic carried on that band must be shifted to the proprietary bands. Customers are sensitive to both the price they pay and the average congestion they experience across the bands of spectrum from which they receive service. We compare two different access policies for this intermittent band: one in which it is open to all SPs and one in which it is licensed to a single SP. We also allow the band to be divided into multiple subbands where each subband is either open or licensed. We characterize trade-offs between social welfare and consumer welfare that depend on the choice of different access policies and assignments of subbands to SPs. These can involve subtle issues related to the ability of a larger SP to make more efficient use of intermittent spectrum and the increase in competition by assigning more spectrum to smaller SPs. This paper was accepted by David Simchi-Levi, operations management.

User Factors Affecting Both Subscription Intention and Time for 4G Wireless Internet Service

While much attention is paid to 4G wireless Internet service based on long term evolution (LTE) technology, the previous studies investigating both subscription intention and of 4G wireless Internet service time are lacking. This study attempts to fill this void by analyzing the subscription intention and time of 4G wireless Internet service users using a bivariate two-equation model. Further, as previous studies on self-efficacy and innovativeness are lacking in mobile service adoption despite the importance of user capability for adopting Internet service, this study intends to fill the void by including user technical competency representing possession of comprehensive knowledge for 4G wireless Internet service, extensive use of wireless Internet, and the use of advanced smart phone. The analysis results of bivariate two-equation model using the sample of 810 Korean users show that if users have the comprehensive knowledge for 4G wireless service, or use advanced mobile smart phone, or greatly use wireless Internet through advanced mobile smart phone, or who are male they are more likely to adopt 4G wireless service. The subscription time is shorter for the users who extensively use wireless Internet and use advanced mobile smart phone or, are male, and have high before tax monthly income. This study contributes to literature in mobile services by suggesting user technical competency as affecting subscription intention and time for 4G wireless Internet service. Managers may better concentrate their marketing efforts to the group of people using wireless Internet extensively and advanced mobile smart phone, and who are male.