Performance evaluation of wake-up radio based wireless body area network

Abstract. The last decade has been really ambitious in new research and development techniques to reduce energy consumption especially in wireless sensor networks (WSNs). Sensor nodes are usually battery-powered and thus have very limited lifetime. Energy efficiency has been the most important aspect to discuss when talking about wireless body area network (WBAN) in particular, since it is the bottleneck of these networks. Medium access control (MAC) protocols hold the vital position to determine the energy efficiency of a WBAN, which is a key design issue for battery operated sensor nodes. The wake-up radio (WUR) based MAC and physical layer (PHY) have been evaluated in this research work in order to contribute to the energy efficient solutions development. WUR is an on-demand approach in which the node is woken up by the wake-up signal (WUS). A WUS switches a node from sleep mode to wake up mode to start signal transmission and reception. The WUS is transmitted or received by a secondary radio transceiver, which operates on very low power. The energy benefit of using WUR is compared with conventional duty-cycling approach. As the protocol defines the nodes in WUR based network do not waste energy on idle listening and are only awakened when there is a request for communication, therefore, energy consumption is extremely low. The performance of WUR based MAC protocol has been evaluated for both physical layer (PHY) and MAC for transmission of WUS and data. The probabilities of miss detection, false alarm and detection error rates are calculated for PHY and the probabilities of collision and successful data transmission for channel access method Aloha is evaluated. The results are obtained to compute and compare the total energy consumption of WUR based network with duty cycling. The results prove that the WUR based networks have significant potential to improve energy efficiency, in comparison to conventional duty cycling approach especially, in the case of low data-reporting rate applications. The duty cycle approach is better than WUR approach when sufficiently low duty cycle is combined with highly frequent communication between the network nodes

Energy efficient scheme based on simultaneous transmission of the local decisions in cooperative spectrum sensing

A common concern regarding cooperative spectrum sensing (CSS) schemes is the occupied bandwidth and the energy consumption during the transmissions of sensing information to the fusion center over the reporting control channels. This concern is intensified if the number of cooperating secondary users in the network is large. This article presents a new fusion strategy for a CSS scheme, aiming at increasing the energy efficiency of a recently proposed bandwidth-efficient fusion scheme. Analytical results and computational simulations unveil a high increase in energy efficiency when compared with the original approach, yet achieving better performances in some situations, and lower implementation complexity

Cooperative Wideband Spectrum Sensing Based on Joint Sparsity

COOPERATIVE WIDEBAND SPECTRUM SENSING BASED ON JOINT SPARSITY By Ghazaleh Jowkar, Master of Science A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University Virginia Commonwealth University 2017 Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering In this thesis, the problem of wideband spectrum sensing in cognitive radio (CR) networks using sub-Nyquist sampling and sparse signal processing techniques is investigated. To mitigate multi-path fading, it is assumed that a group of spatially dispersed SUs collaborate for wideband spectrum sensing, to determine whether or not a channel is occupied by a primary user (PU). Due to the underutilization of the spectrum by the PUs, the spectrum matrix has only a small number of non-zero rows. In existing state-of-the-art approaches, the spectrum sensing problem was solved using the low-rank matrix completion technique involving matrix nuclear-norm minimization. Motivated by the fact that the spectrum matrix is not only low-rank, but also sparse, a spectrum sensing approach is proposed based on minimizing a mixed-norm of the spectrum matrix instead of low-rank matrix completion to promote the joint sparsity among the column vectors of the spectrum matrix. Simulation results are obtained, which demonstrate that the proposed mixed-norm minimization approach outperforms the low-rank matrix completion based approach, in terms of the PU detection performance. Further we used mixed-norm minimization model in multi time frame detection. Simulation results shows that increasing the number of time frames will increase the detection performance, however, by increasing the number of time frames after a number of times the performance decrease dramatically

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin