Location-Based Vertical Handovers in Wi-Fi Networks With IEEE 802.11ah

Abstract

IEEE 802.11ah is a new sub-GHz Wi-Fi technology that provides several advantages over traditional Wi-Fi such as a higher communication range, enhanced scalability, and lower energy consumption, however at the cost of substantially lower throughput. With the aim of simultaneously benefiting from multiple Wi-Fi technologies, recent proposals suggest combining a number of these technologies into a single device. This, however, compromises the energy efficiency of the device, as it implies concurrent utilization of different radio access interfaces. To mitigate this issue, the device should utilize the interface of a certain technology only when there is a high probability of establishing communication over that technology. Traditional vertical handover algorithms are not designed for this purpose as they rely on continuous beacon listening or active probing, even if the device is not in the range of a given technology. To address this issue, vertical handover algorithms based on the combination of devices' physical locations and either Radio Environmental Maps (REM) or propagation modeling have been proposed. Moreover, their suitability and encouraging performance have been demonstrated for a number of the established Low-Power Wide-Area Network (LPWAN) technologies. However, their appropriateness for Wi-Fi-based networks with IEEE 802.11ah is currently unknown, which provides the main motivation for this work. Specifically, we carry out an extensive experimental performance evaluation of two locationbased vertical handover algorithms in the context of Wi-Fi-based networks with IEEE 802.11ah. Our results demonstrate the feasibility of location-based handovers in this context. We base our findings on the fact that location-based algorithms can maintain comparable data communication quality as the beacon listeningbased baseline, while simultaneously reducing the utilization of the IEEE 802.11ah and IEEE 802.11n radio access interfaces by a factor of 2 and 10, respectively.

A Novel Cooperative Relaying-Based Vertical Handover Technique for Unmanned Aerial Vehicles

“…Compute Source node location and velocity (C 0 [mth Slot], V 0 [mth slot]); (5) Deploy relay node at C 0 (m + 1); (6) if Update message of relay fails then (7) Pick another Relay node from pool U i ; T update (8) Update T update � t; (9) endif (10) elseif i ϵ [1, n] then (11) Get update message from source node U 0 ; (12) Compute C i [m + 1]; (13) Synchronize Trajectory along Source node ( 14) endif (15) end for BS reply to Ui with reserve slot for U0; (7) end if (8) else if U0 also Compute BS > RSSI threshold (9) U0 send vertical handover request through Ui (10) BS allocate resource to Uo on behalf of Ui (11) Confirmation sent to relay node Ui and source node U0 (12) U0 initiate authentication (13) BS responds to authentication (14) U0 send confirmation message to relay node (15) end if ALGORITHM 2: Vertical handover using cooperative relaying.…”

“…However, the improved communication among UAVs is restricted by a few primary challenges, such as handover and authentication. In the existing literature [5][6][7], two main techniques are highlighted for handover procedures to change network access technology. First is horizontal handover, in which the same type of network access technology is used to switch communication for end devices.…”

Deep Learning-Based Packet Detection and Carrier Frequency Offset Estimation in IEEE 802.11ah

“…III-A), while outperforming the conventional detector for SNRs below 7 dB. Finally, it is interesting to compare the performance of different algorithms at SNR equal to 10 dB, since the authors in [32] emphasize this SNR value as critical for different IEEE 802.11ah use cases. From Fig.…”

Proactive Cross-Layer Framework Based on Classification Techniques for Handover Decision on WLAN Environments

“…In the first section, you can find protocols that focus on reducing the scanning time such as [19][20][21]; on the other hand, there are proposals that focus on reducing the handover time such as [22,23]. This work focuses on improving decision-making, that is, in point 2.…”