Wireless capsule endoscope (WCE) is a notable invention introduced in the biomedical industry. It involves swallowing a small disposable video capsule that takes photographic images as it passes through the gastrointestinal (GI) tract. WCE allows physicians to visualize and diagnose disorders covering the full length of the GI tract. Although WCE can provide useful images of the internal GI tract, the identification of the exact location of the detected disease remains unclear. Location information is very crucial for the subsequent treatment of the detected disease either through surgery or through local drug delivery. The huge potential of WCE in future endoscopic practice relies on the successful tracking of the wireless capsule. This paper presents a comprehensive systematic review on the recent developments in WCE localization techniques that have been reported in credible sources, namely, IEEE Xplore, PubMed, Scopus, Science Direct, Springer Link, and Google Scholar. Detailed analysis and systematic comparison are provided to highlight the achievement and future direction of WCE localization. This paper can be a valuable source of reference and guidance for future research in this field.

Channel state information (CSI) collected during WiFi packet transmissions can be used for localization of commodity WiFi devices in indoor environments with multipath propagation. To this end, the angle of arrival (AoA) and time of flight (ToF) for all dominant multipath components need to be estimated. A two-dimensional (2D) version of the multiple signal classification (MUSIC) algorithm has been shown to solve this problem using 2D grid search, which is computationally expensive and is therefore not suited for real-time localisation. In this paper, we propose using a modified matrix pencil (MMP) algorithm instead. Specifically, we show that the AoA and ToF estimates can be found independently of each other using the one-dimensional (1D) MMP algorithm and the results can be accurately paired to obtain the AoA–ToF pairs for all multipath components. Thus, the 2D estimation problem reduces to running 1D estimation multiple times, substantially reducing the computational complexity. We identify and resolve the problem of degenerate performance when two or more multipath components have the same AoA. In addition, we propose a packet aggregation model that uses the CSI data from multiple packets to improve the performance under noisy conditions. Simulation results show that our algorithm achieves two orders of magnitude reduction in the computational time over the 2D MUSIC algorithm while achieving similar accuracy. High accuracy and low computation complexity of our approach make it suitable for applications that require location estimation to run on resource-constrained embedded devices in real time.

Intercell interference is one of the most challenging issues in femtocell deployment under the coverage of existing macrocell. Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in dense femtocell networks. Advances in resource management strategies have improved the control mechanism for interference reduction at lower node density, but most of them are ineffective at higher node density. In this paper, a dynamic resource allocation management algorithm (DRAMA) for spectrum shared hybrid access OFDMA femtocell network is proposed. To reduce the macro-femto-tier interference and to improve the quality of service, the proposed algorithm features a dynamic resource allocation scheme by controlling them both centrally and locally. The proposed scheme focuses on Femtocell Access Point (FAP) owners’ satisfaction and allows maximum utilization of available resources based on congestion in the network. A simulation environment is developed to study the quantitative performance of DRAMA in hybrid access-control femtocell network and compare it to closed and open access mechanisms. The performance analysis shows that higher number of random users gets connected to the FAP without compromising FAP owners’ satisfaction allowing the macrocell to offload a large number of users in a dense heterogeneous network.

In this paper, a method to estimate the direction of arrival (DoA) of a radio signal using a multi-element antenna based femtocell device is presented. The femtocell estimates the DoA by identifying the peak of received signal strength indicator (RSSI) measurement using multi-element microstrip antenna. This paper is a modified version of a previously reported work titled as estimation of DoA from radio frequency RSSI measurements using an actuator reflector. In long term evaluation, ultradense deployment of the femtocell device is mainly supported by the intelligent beam forming that translates directly to the constraint of DoA estimation. Use of multi-element antenna over omnidirectional antenna in femtocell is mandated by coverage optimization and reduction of cell overshooting. DoA estimation using microstrip antenna alone is a challenging problem, but it is easier with a multiple number of directive antennas covering the whole plane. Other DoA estimation methods, such as phase arrays, are unsuitable for a small device like femtocell due to the complexity and cost limitations. The proposed method to estimate the DoA is simple enough to be applicable for femtocell indoor applications. Both simulation and experimental results are analyzed to evaluate the performance of the method. Results show that the error in estimated DoA has a mean <;7° and standard deviation <;4°.