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Energy efficiency plays vital roles in wireless communication system due to the "energy limited battery service" of a mobile station (MS). To ensure longer battery life in WiMAX, a new protocol has been introduced in its IEEE802.16m version. This new sleep mode has extended listening window and adjustable sleep cycle length. In this paper, we analyze the probability of attaining at three states: serving state, state of timer inactivity and silent state in a simplified statistical model using traffic parameters of arrival rate, pdf (probability density function) of interarrival time and its threshold value. Finally we developed a new state transition chain of the above three states of a MS of IEEE802.16m and solved the chain in closed form.

Vehicular Ad Hoc Networks (VANETs) is an origination of Mobile Ad-Hoc Network (MANET), where road vehicles will distribute messages and provide safety alerts to notice hazardous circumstances to the drivers. One of its greatest challenges is ensuring Quality of Service (QoS) owing to channel sharing, high traffic and topology changes in VANETs. These challenges cause of degradation of network performance. Congestion control should be properly considered to improve the network performance and transmission message over VANETs. However, there seem significant limitations to most of the other current congestion control mechanisms. In this paper, an enhanced congestion control model based on prioritization and scheduling-based strategy is proposed. This strategy assigns priorities of the safety messages and non-safety messages based of the message type and network condition. Further, safety message can be classified into event-driven messages and beacon messages. At that point, all messages transmit into the appropriate queue based on their priority and schedule all messages in each queue. However, when new message enqueue, reschedule in each queue may cause additional unwanted delay to be processed cause of inefficient scheduling technique. Thus, an improved dynamic scheduling algorithm also proposed to schedule the messages in this circumstance.

Recently power saving is a vital issue for wireless devices of 4G and 5G networks. A device enters in sleeping mode (short and long sleep cycle) when there is no arrival of traffic but wakeup once the arrival of traffic. Before wakeup, the UE user equipment (UE) spends the rest of the sleeping cycle which incurs a delay of service. There is a tradeoff between the length of a sleep cycle (power saving factor ids higher for longer sleep cycle) and mean delay of service. In this paper, a Markov chain is designed including timer inactivity, short sleep, and long sleep and active service states. The closedform solution of the chain is performed using node equations hence comparison of performance is made with previous work in the context of power-saving factor and mean delay. Both the power saving factor and mean delay of this paper are found marginally better than the previous work at lower packet arrival rate but at higher arrival rate performance are almost the same but claims some explanations.

Power saving is one of the key factors of emerging 4G mobile network as well as in IEEE 802.16e wireless metropolitan area networks (Wireless MAN). An efficient power saving mechanism is the heart for the guarantee of a long operating lifetime for a mobile subscriber station (MS), because MSs are normally driven by rechargeable batteries. It is a vital factor for Base Station (BS) of the same network. One of the most important features of 5G mobile is the extension of battery energy 10 times greater than the present days. In this context, the evaluation of duration of sleep mode of BS or MS based on traffic load of a network is now a new era of research work. In this paper, such analysis has been done based on two statistical models: Poisson's pdf and Engset pdf. The concept of complete sharing and partitioning of user group of teletraffic engineering is applied to measure the possibility of getting leisure time of BS or MS. Both the traffic models used in the paper are applicable in both limited and unlimited user network, i.e. in micro and fem to cellular network of 4G and 5G.