Frame-based listen-before-talk (FB-LBT) has been adopted as one of the channel access mechanism for Wi-Fi/LTE coexistence.We aim to explore the limits of FB-LBT by developing theoretical models to characterise the FB-LBT channel access performance under the coexistence of LTE and Wi-Fi.We first derive a steady-state model to calculate the spectrum share occupied by LTE under the assumption that the Wi-Fi transmissions have stationary distributions.The assumption does not hold when the time between two LTE transmissions is short, where the system is dominated by a dynamic phenomenon.A second model is developed that accounts for the dynamics of the Wi-Fi channel access mechanism.Our models, validated by simulation results, accurately calculate the spectrum share occupied by LTE over a range of FB-LBT frame periods and Wi-Fi traffic loads.We obtain upper bounds on the FB-LBT spectrum share when competing with heavy Wi-Fi traffic, which confirm the weakness of FB-LBT.Moreover, we demonstrate that our models can be used to control the FB-LBT spectrum share within a modest range.

The existence of relatively long LTE data blocks within the licensed-assisted access (LAA) framework results in bursty machine-type communications (MTC) packet arrivals, which cause system performance degradation and present new challenges in Markov modeling. We develop an embedded Markov chain to characterize the dynamic behavior of the contention arising from bursty MTC and Wi-Fi data traffic in the LAA framework. Our theoretical model reveals a high-contention phenomenon caused by the bursty MTC traffic, and quantifies the resulting performance degradation for both MTC and Wi-Fi data traffic. The Markov model is further developed to evaluate three potential solutions aiming to alleviate the contention. Our analysis shows that simply expanding the contention window, although successful in reducing congestion, may cause unacceptable MTC data loss. A TDMA scheme instead achieves better MTC packet delivery and overall throughput, but requires centralized coordination. We propose a distributed scheme that randomly spreads the MTC access processes through the available time period. Our model results, validated by simulations, demonstrate that the random spreading solution achieves a near TDMA performance, while preserving the distributed nature of the Wi-Fi protocol. It alleviates the MTC traffic contention and improves the overall throughput by up to 10%.

Large scale deployment of machine-to-machine (M2M) communication networks hinges on the cost and energy efficient design of the embedded devices. Standard WLAN power save mechanisms, which are designed for human communications, experience performance degradation and unbalanced energy consumptions in M2M communication networks. We develop a novel analytical model that takes into account the fundamentally different network architecture and traffic patterns of M2M communications. Our model accurately characterizes the high contention and long packet delay found in M2M communication networks, while previous models underestimate such measures. To combat such performance decline, we propose a new algorithm that enhances existing power save mechanisms to extend the lifetime of a M2M communication network. We call this the Offset ListenInterval (OLi) Algorithm. The OLi algorithm spreads the M2M traffic evenly with calculated offsets to alleviate network contention and reduce packet delay. Our analytical model is then used to evaluate the energy efficiency of our OLi algorithm and compare with the standard power save mechanisms. Our results show that the proposed OLi algorithm extends the lifetime by up to 40%, and scales up to thousands of nodes in a M2M communication network.

Communication is an enabling technology for the efficient control and management of next-generation Smart Grids. Energy conservation of the communication devices is essential for future large scale deployment of Smart Grid communication networks. However, existing power save protocols experience high contention in Smart Grid communication networks that have a large number of nodes and periodic traffic. We design a new energy conservation protocol, Power Save with Offset Listen Interval (PS-OLi), to address such contention problems. PS-OLi avoids message collisions by controlling the station wake up time with a calculated offset. A new analytical model is developed to characterize the power save performance of networks with periodic traffic. Simulation results show that our analytical model accurately predicts the collision probability and packet delay. We use our model to evaluate the energy efficiency of PS-OLi and standard power save protocols. Our results show that PS-OLi extends the lifetime of a Smart Grid communication network by more than 10%.

In practical radio transmissions, bit error and channel capture are two dominating factors that affect wireless network performance. Previous models have omitted the interaction between bit error and channel capture. We present a homogeneous-network performance-prediction model for a Rayleigh fading channel that incorporates both the capture effect and transmission error into a 3-D Markov Chain. We accurately characterise the interaction between packet error and capture by incorporating them both into the model of the receiver operations. We show how the model can be solved efficiently. The model provides quality of service measures, including packet delay and loss, which are difficult to achieve with other models. Simulation results confirm that our 3-D model accurately predicts the performance for practical SNRs and receiver sensitivities. We demonstrate that our model can be directly applied to call admission control of Voice over IP service with a QoS guarantee in a WiFi network. The model is then extended to heterogeneous networks, where different stations have different packet arrival rates and packet sizes.

The authors of the above titled paper (ibid., vol. 9, no. 8, pp. 2664-2675, Aug. 2010), have become aware that several of the equations in that paper were presented with errors. In this brief, we provide correct equations. The implementation of the model in the original paper was in accordance with the correct equations, so the implementation results presented in Section V. Performance Analysis are still valid.

We consider the impacts of channel fading on the quality of service (QoS) performance of the IEEE 802.11 system. Traditional 2-D Markov chain models, while suitable for throughput analysis, are unable to capture the QoS performance due to the lack of a proper queueing model. We present a 3-D Markov chain queueing model that incorporates channel fading effects and solve the Markov chain efficiently with our Collapsed Transition onto Basis approach. In doing so, we are able to investigate important QoS measures, packet delay and loss, as well as throughput, for a 802.11 system under practical channel fading conditions. The analytical results are validated by extensive simulations. Our 3-D model offers new insights in channel fading effects on system capacity and QoS performance. We demonstrate that our 3-D model can also be used to provides guidelines for traffic control.

The capture effect can occur in IEEE 802.11 distributed coordination function (DCF) wireless systems when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a network performance prediction model that accurately incorporates the capture effect into a 3-D Markov Chain. The model is solved efficiently with the Collapsed Transition onto Basis (CTB) approach. The performance of the model is significantly better than existing models in terms of estimating important QoS measures, including packet delay and loss, as well as collision probability and throughput.

Quality of Service (QoS) and queue management are important issues for IEEE 802.11 systems. However, existing 2-dimensional (2-D) Markov chain models of 802.11 systems are unable to capture the complete QoS performance and queueing behavior due to the lack of an adequate finite buffer model. We present a 3-dimensional (3-D) Markov chain that integrates the 802.11 system contention resolution and queueing processes into one model. The 3rddimension, that models the queue length, allows us to accurately capture important QoS measures, delay and loss, plus throughput and queue length, for realistic 802.11 systems with finite buffer under finite load. We derive an efficient method for solving the steady state probabilities of the Markov chain. Our 3-D Markov chain is the first finite buffer model defined and solved for 802.11 systems. The solutions, validated by extensive simulations, capture the system dynamics over a wide range of traffic load, buffer capacity, and network size. Our 3-D model points to the existence of an effective maximum throughput and shows its relationship with buffer capacity. We demonstrate that our 3-D model can also be used in resource allocation to determine adequate buffer sizes under a particular QoS constraint.

We introduce a 3-dimensional Markov chain that integrates the IEEE 802.11 DCF contention resolution and queueing processes into one model. Important QoS measures, delay and loss, plus throughput and queue length, can be obtained for a realistic systems with finite buffer under finite load. We present an efficient method for solving the steady state probabilities of the Markov chain. Simulations confirm the accuracy of our model, and demonstrate that the model provides new insights into the 802.11 DCF protocol.