Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence.
The millimeter-wave (mmWave) is expected to deliver a huge bandwidth to address the future demands for higher data rate transmissions. However, one of the major challenges in the mmWave band is the increase in signal loss as the operating frequency increases. This has attracted several research interests both from academia and the industry for indoor and outdoor mmWave operations. This paper focuses on the works that have been carried out in the study of the mmWave channel measurement in indoor environments. A survey of the measurement techniques, prominent path loss models, analysis of path loss and delay spread for mmWave in different indoor environments is presented. This covers the mmWave frequencies from 28 GHz to 100 GHz that have been considered in the last two decades. In addition, the possible future trends for the mmWave indoor propagation studies and measurements have been discussed. These include the critical indoor environment, the roles of artificial intelligence, channel characterization for indoor devices, reconfigurable intelligent surfaces, and mmWave for 6G systems. This survey can help engineers and researchers to plan, design, and optimize reliable 5G wireless indoor networks. It will also motivate the researchers and engineering communities towards finding a better outcome in the future trends of the mmWave indoor wireless network for 6G systems and beyond.
In future 5G systems, the millimeter wave (mmWave) band will be used to support a large capacity for current mobile broadband. Therefore, the radio access technology (RAT) should be made available for 5G devices to help in distinct situations, for example device-to-device communications (D2D) and multi-hops. This paper presents ultra-wideband channel measurements for millimeter wave bands at 19, 28, and 38 GHz. We used an ultra-wideband channel sounder (1 GHz bandwidth) in an indoor to outdoor (I2O) environment for non-line-of-sight (NLOS) scenarios. In an NLOS environment, there is no direct path (line of sight), and all of the contributed paths are received from different physical objects by refection propagation phenomena. Hence, in this work, a directional horn antenna (high gain) was used at the transmitter, while an omnidirectional antenna was used at the receiver to collect the radio signals from all directions. The path loss and temporal dispersion were examined based on the acquired measurement data—the 5G propagation characteristics. Two different path loss models were used, namely close-in (CI) free space reference distance and alpha-beta-gamma (ABG) models. The time dispersion parameters were provided based on a mean excess delay, a root mean square (RMS) delay spread, and a maximum excess delay. The path loss exponent for this NLOS specific environment was found to be low for all of the proposed frequencies, and the RMS delay spread values were less than 30 ns for all of the measured frequencies, and the average RMS delay spread values were 19.2, 19.3, and 20.3 ns for 19, 28, and 38 GHz frequencies, respectively. Moreover, the mean excess delay values were found also at 26.1, 25.8, and 27.3 ns for 19, 28, and 38 GHz frequencies, respectively. The propagation signal through the NLOS channel at 19, 28, and 38 GHz was strong with a low delay; it is concluded that these bands are reliable for 5G systems in short-range applications.
Long Range Wide Area Network (LoRaWAN) is one of the most promising IoT technologies that are widely adopted in low-power wide-area networks (LPWAN). LoRaWAN faces scalability issues due to a large number of nodes connected to the same gateway and sharing the same channel. Therefore, LoRa networks seek to achieve two main objectives: successful delivery rate and efficient energy consumption. This paper proposes a novel game theoretic framework for LoRaWAN named Best Equal LoRa (BE-LoRa), to jointly optimize the packet delivery ratio and the energy efficiency (bit/Joule). The utility function of LoRa node is defined as the ratio of the throughput to the transmit power. LoRa nodes act as rational users (players) which seek to maximize their utility. The aim of the BE-LoRa algorithm is to maximize the utility of LoRa nodes while maintaining the same signal-to-interference-and-noise-ratio (SINR) for each SF. The power allocation algorithm is implemented at the network server, which leads to an optimum SINR, spreading factors (SFs) and transmission power settings of all nodes. Numerical and simulation results show that the proposed BE-LoRa power allocation algorithm has a significant improvement in packet delivery ratio and energy efficiency as compared to the Adaptive Data Rate (ADR) algorithm of legacy LoRaWAN. For instance, in very dense networks (624 nodes), BE-LoRa can improve the delivery ratio by 17.44% and reduce power consumed by 46% compared with LoRaWAN ADR.
The design of traditional mobile wireless network emphasises on large capacity as well as ubiquitous access. However, environmental protection and energy saving may soon become inevitable trends due to rising global demands. In the wireless networking field, researchers should shift their focus towards efficient networks and energy harvesting (EH). In this work, we consider energy efficiency and EH to address the issue of energy shortage, which also represents the ratio of the quantity of data that have been transferred to the dissipated energy within the system, simultaneously. The simulation-based mathematics signifies the relation between energy efficiency () against the training interval () and how the energy efficiency is impacted by the change in block size and number of users.
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