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The conventional outage in wireless communication systems is caused by the deterioration of the wireless communication link, i.e., the received signal power is less than the minimum received signal power. Is there a possibility that the outage occurs in wireless communication systems with a good channel state? Based on both communication and heat transfer theories, a power-consumption outage in the wireless communication between millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) base stations (BSs) and smartphones has been modeled and analyzed. Moreover, the total transmission time model with respect to the number of power-consumption outages is derived for mmWave massive MIMO communication systems. Simulation results indicate that the total transmission time is extended by the power-consumption outage, which deteriorates the average transmission rate of mmWave massive MIMO BSs.
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Prior Internet designs encompassed the fixed, mobile and lately the things Internet. In a natural evolution to these, the notion of the Tactile Internet is emerging which allows one to transmit touch and actuation in real-time. With voice and data communications driving the designs of the current Internets, the Tactile Internet will enable haptic communications, which in turn will be a paradigm shift in how skills and labor are digitally delivered globally. Design efforts for both the Tactile Internet and the underlying haptic communications are in its infancy. The aim of this article is thus to review some of the most stringent design challenges, as well as proposing first avenues for specific solutions to enable the Tactile Internet revolution.
One of the limitations of wireless sensor nodes is their inherent limited energy resource. Besides maximizing the lifetime of the sensor node, it is preferable to distribute the energy dissipated throughout the wireless sensor network in order to minimize maintenance and maximize overall system performance. We investigate a new routing algorithm that uses diffusion in order to achieve relatively even power dissipation throughout a wireless sensor network by making good local decisions. We leverage from concepts of peer-to-peer networks in which the system acts completely decentralized and all nodes in the network are equal peers. Our algorithm utilizes the node load, power levels, and spatial information in order to make the optimal routing decision. According to our preliminary experimental results, our proposed algorithm performs well according to its goals.
Emerging 5G and next generation 6G wireless are likely to involve myriads of connectivity, consisting of a huge number of relatively smaller cells providing ultra-dense coverage. Guaranteeing seamless connectivity and service level agreements in such a dense wireless system demands efficient network management and fast service recovery. However, restoration of a wireless network, in terms of maximizing service recovery, typically requires evaluating the service impact of every network element. Unfortunately, unavailability of real-time KPI information, during an outage, enforces most of the existing approaches to rely significantly on context-based manual evaluation. As a consequence, configuring a real-time recovery of the network nodes is almost impossible, thereby resulting in a prolonged outage duration. In this article, we explore deep learning to introduce an intelligent, proactive network recovery management scheme in anticipation of an eminent network outage. Our proposed method introduces a novel utilization-based ranking scheme of different wireless nodes to minimize the service downtime and enable a fast recovery. Efficient prediction of network KPI (Key Performance Index), based on actual wireless data demonstrates up to ~54% improvement in service outage.
Recent years have witnessed the proliferation of Low-power Wide Area Networks (LPWANs) in the unlicensed band for various Internet-of-Things (IoT) applications. Due to the ultra-low transmission power and long transmission duration, LPWAN devices inevitably suffer from high power Cross Technology Interference (CTI), such as interference from Wi-Fi, coexisting in the same spectrum. To alleviate this issue, this paper introduces the Partial Symbol Recovery (PSR) scheme for improving the CTI resilience of LPWAN. We verify our idea on LoRa, a widely adopted LPWAN technique, as a proof of concept. At the PHY layer, although CTI has much higher power, its duration is relatively shorter compared with LoRa symbols, leaving part of a LoRa symbol uncorrupted. Moreover, due to its high redundancy, LoRa chips within a symbol are highly correlated. This opens the possibility of detecting a LoRa symbol with only part of the chips. By examining the unique frequency patterns in LoRa symbols with time-frequency analysis, our design effectively detects the clean LoRa chips that are free of CTI. This enables PSR to only rely on clean LoRa chips for successfully recovering from communication failures. We evaluate our PSR design with real-world testbeds, including SX1280 LoRa chips and USRP B210, under Wi-Fi interference in various scenarios. Extensive experiments demonstrate that our design offers reliable packet recovery performance, successfully boosting the LoRa packet reception ratio from 45.2% to 82.2% with a performance gain of 1.8 times.
To cope with the explosive traffic growth of next-generation wireless communications, it is necessary to design next-generation multiple access techniques that can provide higher spectral efficiency as well as larger-scale connectivity. As a promising candidate, power-domain non-orthogonal multiple access (NOMA) has been widely studied. In conventional power-domain NOMA, multiple users are multiplexed in the same time and frequency band by different preset power levels, which, however, may limit the spectral efficiency under practical finite alphabet inputs. Inspired by the concept of spatial modulation, we propose to solve this problem by encoding extra information bits into the power levels, and exploit different signal constellations to help the receiver distinguish between them. To convey this idea, termed power selection (PS)-NOMA, clearly, we consider a simple downlink two-user NOMA system with finite input constellations. Assuming maximum-likelihood detection, we derive closed-form approximate bit error ratio (BER) expressions for both users. The achievable rates of both users are also derived in closed form. Simulation results verify the analysis and show that the proposed PS-NOMA outperforms conventional NOMA in terms of BER and achievable rate.
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