In this paper, we propose a low-power, high-speed, multi-carrier reconfigurable transceiver based on Frequency Division Multiplexing to ensure data transfer in future Wireless NoCs. The proposed transceiver supports a medium access control method to sustain unicast, broadcast and multicast communication patterns, providing dynamic data exchange among wireless nodes. The proposed transceiver designed using a 28-nm FDSOI technology consumes only 2.37 mW and 4.82 mW in unicast/broadcast and multicast modes, respectively, with an area footprint of 0.0138 mm2.

Wireless Networks-on-Chip (WiNoC) are being explored for parallel applications to improve the performances by reducing the long distance/critical path communications. However, WiNoC still require precise propagation models to go beyond proof of concept and to demonstrate it can be considered as a realistic efficient alternative to wired NoC. In this paper, we present accurate 3D models based on measurements in Ka band and Electromagnetic (EM) simulations of transmission on silicon substrate in the V band and the Sub-THz band. Using these EM results, a time-domain simulation is performed using an On-Off Keying (OOK) modulation based transmission with different PA/LNA configurations. Our results highlight the type of performances and tradeoffs to be considered according to different parameters such as power output and amplifier's gain. By improving the knowledge about the signal propagation, one can conduct precise design space exploration for parallel applications. We discuss the realistic channel modeling and we present also hybrid solutions and associated limitations of WiNoC architectures. We conclude the paper with research directions to be explored to make WiNoC a reality.

Wireless Network-on-Chip (WiNoC) is one of the most promising solutions to overcome multi-hop latency and high power consumption of modern many/multi core System-on-Chip (SoC). However, the design of efficient wireless links faces challenges to overcome multi-path propagation present in realistic WiNoC channels. In order to alleviate such channel effect, this paper presents a Time-Diversity Scheme (TDS) to enhance the reliability of on-chip wireless links using a semi-realistic channel model. First, we study the significant performance degradation of state-of-the-art wireless transceivers subject to different levels of multi-path propagation. Then we investigate the impact of using some channel correction techniques adopting standard performance metrics. Experimental results show that the proposed Time-Diversity Scheme significantly improves Bit Error Rate (BER) compared to other techniques. Moreover, our TDS allows for wireless communication links to be established in conditions where this would be impossible for standard transceiver architectures. Results on the proposed complete transceiver, designed using a 28-nm FDSOI technology, show a power consumption of 0.63mW at 1.0V and an area of 317 μm2. Full channel correction is performed in one single clock cycle.

This paper addresses the issue of low-power posture and gesture recognition in indoor or outdoor environments without any additional equipment. For applications based on predefined postures such as environment control and physical rehabilitation, we show that low cost and fully distributed solutions, that minimize radio communications, can be efficiently implemented. Considering that radio links provide distance information, we also demonstrate that the matrix of estimated inter-node distances offers complementary information that allows for the reduction of communication load. Our results are based on a simulator that can handle various measured input data, different algorithms and various noise models. Simulation results are useful and used for the development of real-life prototype.

A body network of Inertial Measurement Units (IMUs) is a well known solution for posture recognition based on accelerometer and magnetometer data fusion. However sensors and especially the magnetometer can be disturbed by the environment. Considering a Wireless Body Sensor Network (WBSN), we propose to use available radio received power measurements as an alternative to the magnetometer. We show with simulation and real data, that the radio signal used for WBSN communications can also provide useful location information despite highly noisy Received Signal Strength Indications (RSSI). We propose a solution for the static case that leads to a very simple yet Efficient algorithm.

This letter proposes a quasi optimum maximum likelihood detection technique based on Geometrical Diversification and Greedy Intensification (GDGI). The presented detector scheme is shown to achieve almost optimal performance for all signal-to-noise ratio (SNR) values and a cubic computation complexity in the problem dimension. It possesses a regular structure well suited for hardware implementation. Simulation results show that for a system with a high dimension of n = 60, the loss is approximately 0.35 dB at BER=10-5compared to an optimal decoding.

An efficient sub-optimal algorithm, called HIS (hyperplane intersection and selection) detection algorithm, is proposed to solve the problem of joint detection of K users in an MC-CDMA system. Compared to existing solutions, the proposed algorithm has three characteristics very attractive for practical. systems. Firstly, it has nearly optimal performance. Secondly, it has a low computational complexity - O(K/sup 2/) multiplications and O(K/sup 3/) additions. Third, the algorithm has an inherent parallelism. To our knowledge, the HIS algorithm is not just an add-on to an existing algorithm, but rather a new decoding technique based on a singular value decomposition of the channel matrix, H. After giving the equation of the MC-CDMA multi-user detection problem, the HIS algorithm is described. Its performance is compared to known existing algorithms (ZF, MMSE, PIC and sphere decoding). For a BER as low as 10/sup -4/, the HIS algorithm introduces only 0.2 dB degradation compared to the optimal sphere decoding algorithm for K=16 users against 3.8 dB for the PIC algorithm with two MMSE stages.