Sami Khairy

Performance Analysis of Opportunistic Channel Bonding in Multi-Channel WLANs

In this paper, an analytical framework is developed to study the performance of opportunistic channel bonding in IEEE 802.11 WLANs. Specifically, we consider a WLAN operating on multiple channels shared by both legacy users and IEEE 802.11ac users with channel bonding capability. By capturing the opportunistic channel bonding from the IEEE 802.11ac users in the primary channel and the random access of legacy users in the secondary channels, we derive the successful channel bonding probability, and the throughput of both legacy and IEEE 802.11ac users. Our analysis shows that with multi-channel bonding, ac users achieves a higher throughput at the cost of reduced throughput of legacy users in the secondary channels. The channel bonding achieves a higher total network throughput only when there is no legacy user in the secondary channels, and the total throughput decreases when legacy users exist due to the increased contentions in the secondary channels. The analysis provides important guidance for the deployment of multi-channel WLANs where ac users should select a proper primary channel to maximize its bonding opportunity and to attain the maximum throughput. Extensive simulations are conducted to validate the analysis.

Enabling efficient multi-channel bonding for IEEE 802.11ac WLANs

In this paper, an analytical model is developed to study the performance of distributed and opportunistic multichannel bonding in IEEE 802.11ac WLANs, with co-existing legacy IEEE 802.11a/b/g users. By modeling the transmissions of legacy users and ac users with and without channel bonding in each channel as a two-level renewal process, the channel bonding probability of ac users in each secondary channel is derived. Based on the bonding probability, the throughput of legacy users and ac users can be analyzed respectively. Our analysis shows that ac users with bonding capabilities achieve higher throughput at the cost of degraded throughput of legacy users. The overall network throughput also decreases due to the increased contention level imposed by ac users in secondary channels. Based on the analysis, we further propose a channel selection scheme for ac users to select the best primary channel, in order to mitigate the contentions in the network and attain the maximal network throughput. Extensive simulations using NS-3 validate the analysis and demonstrate the efficiency of the proposed channel selection scheme.

Radio Access Management of U-LTE

Next generation 5G networks will support not only emerging services, but also other services which may be beyond our imagination today. Improving the system capacity remains nevertheless one of the most important targets of 5G. Long Term Evolution (LTE) operation over the unlicensed band (U-LTE) is considered as one promising solution to achieve this target. In this chapter, we introduce the state of the art coexistence technologies of U-LTE with other unlicensed systems. Specifically, we investigate the coexistence of LTE Licensed Assisted Access (LAA; LAA is the preferred mode of operation for U-LTE and was newly released in 2015) with Wi-Fi over the unlicensed band. To this end, we first develop an analytical model to study the performance of the existing Load Based Equipment (LBE) MAC for LAA, identify the fairness issues, and quantify the reservation overhead of the protocol. Next, we propose a hybrid MAC protocol for LAA to maximize the network throughput, by minimizing LAA MAC reservation overhead while ensuring fair spectrum sharing of U-LTE and Wi-Fi. To achieve the best coexistence performance, a two-level renewal process-based model is developed to analyze the proposed MAC and optimize its parameters. Extensive simulations using NS-3 are conducted to validate the analysis and demonstrate the efficiency of the proposed MAC protocol.

Game Theory Based Spectrum Sharing

LTE unlicensed brings high Quality of Service (QoS) to all mobile users. However, when there are multiple wireless cellular operators trying to access the unlicensed spectrum simultaneously, due to the autonomous behaviors of each operator, it is important yet challenging to avoid malicious competitions among all operators, while guaranteeing the performance of other networks in the unlicensed spectrum. In this chapter, game theory is introduced and applied as a powerful tool to deal with the spectrum sharing problem among multiple operators. Considering the relations among all the operators and the Wi-Fi Access Point (WAP), a layered power control game is modeled, where we first fix the behaviors of all other operators, and propose the zero-determinant strategy for the power control of one considered operator. Based on the predicted strategies of every operator in all situations, all operators then play a non-cooperative game and determine their optimal strategies to achieve the Nash equilibrium results.

Traffic Offloading from Licensed Band to Unlicensed Band

Due to the limited amount of licensed spectrum and increasing wireless data transmission requirements, the service offloading from licensed spectrum to unlicensed spectrum significantly improves the Quality of Service (QoS) of mobile users. Nevertheless, in the scenarios of multiple operators and multiple user equipments (UEs), considering the various requirements and locations of UEs, how to manage the spectrum allocation of licensed and unlicensed spectrum remains challenging. In this chapter, considering the distributive behaviors of all operators and UEs, a multi-operator multi-UE Stackelberg game is implemented to analyze the interaction between multiple operators and their subscribing UEs. In this game, to avoid intolerable interference to the Wi-Fi Access Point (WAP), each operator sets an interference penalty price for each UE that causes interference to the WAP, and the UEs can choose their sub-bands and determine the optimal transmit power in the chosen sub-bands of the unlicensed spectrum. Accordingly, the operators can predict the possible actions of UEs, and hence set the optimal prices to maximize its revenue. Furthermore, we consider two possible scenarios for the interaction of operators in the unlicensed spectrum. In the first scenario, referred to as the non-cooperative scenario, the operators cannot coordinate with each other in the unlicensed spectrum. A sub-gradient approach is applied for each operator to decide its best-response action based on the possible behaviors of others. In the second scenario, referred to as the cooperative scenario, all operators can coordinate with each other to serve UEs and control the UEs’ interference in the unlicensed spectrum. Simulation results have been presented to verify the performance improvement that can be achieved by our proposed schemes.

Spectrum Matching in Unlicensed Band with User Mobility

By integrating the unlicensed spectrum with the licensed spectrum, users of U-LTE can experience enhanced transmission, while maintaining the seamless mobility management and predictable performance. However, due to different transmission regulations, the coordination between LTE and Wi-Fi systems requires careful design. Especially, it’s important to understand how to guarantee the transmission quality for LTE users and reduce Wi-Fi users’ performance degradation, under the impact of the co-channel interference. In this chapter, we propose a matching theory framework to tackle this problem. Specifically, the coexistence between LTE and Wi-Fi systems, i.e., the interaction between LTE and Wi-Fi users, is modeled as the stable marriage (SM) game. The coexistence constraints are interpreted as the preference lists. Two semi-distributed solutions, namely the Gale-Shapley (GS) and the Random Path to Stability (RPTS) algorithms are proposed. What’s more, to address the external effect in matching, the Inter-Channel Cooperation algorithm is introduced. Last but not least, the resource allocation problem is studied with network dynamics, and the proposed mechanisms are evaluated under two typical user mobility models.