No abstract

To keep pace with the current rapid evolution of mobile data requirements, IEEE 802.11 was evolved to provide more desirable performance to fulfill the needs of fifth-generation (5G) and Internet of Things (IoT) networks. It provides two different access contention-based schemes; Distributed Coordination Function (DCF) which not differentiates between different services, and Enhanced Distributed Channel Access (EDCA) which provides differentiation between various services through four priority Access Categories (ACs). The dilemma of the conventional IEEE 802.11 networks is the static assignation of parameters in DCF and EDCA regardless of the number of associated stations and no matter what kind of service is required by each station (i.e., the activity of ACs). Consequently, this led to a significant degradation in the performance of the network, especially in the case of ultra-dense load network. Therefore, in this paper, we introduce a novel algorithm for EDCA considering a dynamic assignation of Arbitration Inter-Frame Space Number (AIFSN) and guidance Contention Window (CW) depending on the number of associated stations and ACs activeness status. Based on the analytical models of EDCA, a game-theoretic method is proposed to make each associated station adapts its transmission probability within the guidance CW. The purpose of guidance CW is a pre-stage to detect the selfish stations which pick up a very low CW to maximize its throughput regardless of the overall network throughput. Simulation results show that the proposed game-based algorithm can obtain higher performance than the standard 802.11 networks in terms of normalized throughput, data dropped during retransmissions limit threshold exceeding, and mean average delay for sensitive delay applications. INDEX TERMS EDCA, high density WLANs, multiple access, selfish nodes, 5G.

IEEE 802.11 networks have a great role to play in supporting and deploying of the Internet of Things (IoT). The realization of IoT depends on the ability of the network to handle a massive number of stations and transmissions and to support Quality of Service (QoS). IEEE 802.11 networks enable the QoS by applying the Enhanced Distributed Channel Access (EDCA) with static parameters regardless of existing network capacity or which Access Category (AC) of QoS is already active. Our objective in this paper is to improve the efficiency of the uplink access in 802.11 networks; therefore we proposed an algorithm called QoS Categories Activeness-Aware Adaptive EDCA Algorithm (QCAAAE) which adapts Contention Window (CW) size, and Arbitration Inter-Frame Space Number (AIFSN) values depending on the number of associated Stations (STAs) and considering the presence of each AC. For different traffic scenarios, the simulation results confirm the outperformance of the proposed algorithm in terms of throughput (increased on average 23%) and retransmission attempts rate (decreased on average 47%) considering acceptable delay for sensitive delay services.

To provide enhanced mobile services, the 5G system is expected to further densify its network infrastructure and scale up the deployment of massive antenna arrays that emit highenergy beams using the millimeter wave spectrum. These radically new features will significantly impact the EMF exposure level in the 5G networks. In this paper, EMF exposure for 5G mobile networks in a dense urban environment is investigated using a raytracing approach for the uplink (UL) and downlink (DL). A massive multi-input multi-output antenna with multiuser beamforming capability is considered for the 5G base station. For DL, the maximum rate transmission (MRT) technique is used to direct the beams toward all the active users, and total power density (PD) is used to evaluate the EMF exposure level. On the other hand, EMF exposure due to UL is investigated using electric field strength and specific absorption rate (SAR). The proposed ray-tracing based EMF evaluation framework exploits detailed information of the scenarios, including 3D building geometry, EM characteristics, multipath propagation, user locations and beamforming radiation pattern, to effectively evaluate the EMF's spatial variation levels. Following this evaluation procedure, the impact of different user densities and distributions is analyzed in terms of PD and SAR. Results show that for DL, the peak PD increases from 6.65 to 24.92 dBm/m 2 when the number of active users in the area increases from a single user to 100%. Considering the worst-case scenario, the PD exposure reaches 62% of the ICNIRP's limit. Saturation of the spatial EMF distribution occurs when the number of active DL beams is above 25%. For UL, within 5m radius of the user's location, the average E-field may increase from 2.40 to 3.98 V/m. (increment of 66%) if the number of active users in the area increases from 25% to 100%. Moreover, when 100% of the users are actively transmitting, there is only a 10% probability that the SAR may exceed 0.06 W/kg (or 3% of the ICNIRP's limit).

Despite the rapid growth in the market demanding for wireless sensor networks (WSNs), they are far from being secured or efficient. WSNs are vulnerable to malicious attacks and utilize too much power. At the same time, there is a significant increment of the security threats due to the growth of the several applications that employ wireless sensor networks. Therefore, introducing physical layer security is considered to be a promising solution to mitigate the threats. This paper evaluates popular coding techniques like Reed solomon (RS) techniques and scrambled error correcting codes specifically in terms of security gap. The difference between the signal to nose ratio (SNR) of the eavesdropper and the legitimate receiver nodes is defined as the security gap. We investigate the security gap, energy efficiency, and bit error rate between RS and scrambled t-error correcting codes for wireless sensor networks. Lastly, energy efficiency in RS and Bose-Chaudhuri-Hocquenghem (BCH) is also studied. The results of the simulation emphasize that RS technique achieves similar security gap as scrambled error correcting codes. However, the analysis concludes that the computational complexities of the RS is less compared to the scrambled error correcting codes. We also found that BCH code is more energy-efficient than RS.