We investigate optimal call admission control (CAC) policy for multicast streaming services (MSS) in 3rd generation (3G) and beyond wireless mobile networks. Several MSS sessions are supported simultaneously in a bandwidth-limited network. Active sessions are those that are currently serving some users, and inactive sessions are those that are currently not serving any users. An admission decision in MSS is required only when an inactive session is requested, unlike in unicasting. For this reason, if a user request for an inactive MSS session arrives, we should make an admission decision in anticipation of (i) the possible reward earned based on users served during a session active time generated by accepting it, and (ii) the influence of the session active time upon the future status of network bandwidth and admission decisions. Our objective is to determine when to admit or block a user asking an inactive MSS session to achieve the optimality in rewards. We formulate this problem as a semi-Markov decision process (SMDP), and a value iteration algorithm is used to obtain an optimal stationary deterministic policy. We also derive the user blocking probability of the optimal policy by analyzing an embedded Markov chain induced by it.

This paper considers random access protocols with multipacket reception (MPR), which include both slotted-Aloha and slotted τ-persistent CSMA protocols. For both protocols, each node makes a transmission attempt in a slot with a given probability. The goals of this paper are to derive the optimal transmission probability maximizing a system throughput for both protocols and to develop a simple random access protocol with MPR, which achieves a system throughput close to the maximum value. To this end, we first obtain the optimal transmission probability of a node in the slotted-Aloha protocol. The result provides a useful guideline to help us develop a simple distributed algorithm for estimating the number of active nodes. We then obtain the optimal transmission probability in the τ-persistent CSMA protocol. An in-depth study on the relation between the optimal transmission probabilities in both protocols shows that under certain conditions the optimal transmission probability in the slotted-Aloha protocol is a good approximation for the τ-persistent CSMA protocol. Based on this result, we propose a simple τ-persistent CSMA protocol with MPR which dynamically adjusts the transmission probability τ depending on the estimated number of active nodes, and thus can achieve a system throughput close to the maximum value.

In this paper, we propose an new admission control scheme jointly taking into account call-level QoS based on the dropping probability of handoff call and packet-level QoS based on the outage probability over threshold in IEEE 802.16e where user mobility is allowed and adaptive modulation and coding (AMC) is employed. The proposed admission control scheme is characterized by both a threshold for handoff calls at call-level and the outage probability over threshold at packet-level. First, we investigate the outage probability over threshold at packet-level. In order to determine the threshold, we derive the dropping probability of handoff call by using Markov chain model at call-level. Numerical results show that our proposed admission control scheme protects well the quality of service (QoS) of ongoing calls including handoff calls.

We develop an analytical model to investigate the performance of a decentralized MAC protocol based on IEEE 802.11 DCF for cognitive radio networks with single spectrum band. Our analysis provides the throughput obtained by secondary users and the interference ratio perceived by primary users (SUs). The theoretical approach is verified by comparing its numerical results to simulation results. Numerical and simulation results depict the fundamental properties on the performance under various network parameters such as the number of SUs, the packet size of SUs and the minimum contention window size.

We investigate the delay of the bandwidth request under the truncated binary exponential backoff (TBEB) mechanism in the IEEE 802.16e, considering error-free/error- prone wireless channels. We derive the distribution of delay of bandwidth request packets in the TBEB by an analytic method on the assumption of Bernoulli request arrival process and error-free channel conditions, and extend the analytic results to the error-prone channel condition where the request transmissions have error with i.i.d. By numerical analysis we can find the optimal number of transmission opportunities for transmitting bandwidth requests of the TBEB satisfying QoS on delay bound and loss bound.

First, we propose a new modeling method for superposed ATM traffic by the MMPP(2), which is a special case of the MAP(2). In this new method, we measure the mean and autocorrelation of cell interarrival times, and the histogram of the number of arrivals during measurement windows of fixed size. The MMPP(2) has interarrival times with a second-order hyper-exponential distribution with coefficient of variation c/sub /spl nu// > 1. However, superposed traffic is often observed to have c/sub /spl nu// < 1. To cover this situation, we extend the MMPP(2) to a MAP(3) by adding a new state with inter-state transition accompanied by an arrival. For the MAP(3) model, we take into account the second moment of the interarrival times. From numerical examples, we observe that both the proposed MMPP(2) and MAP(3) yields very good estimation of the cell loss ratio (CLR) for usual superpositions of voice and/or VBR video sources. However, when we have superpositions from CBR video sources together with other VBR sources, c/sub /spl nu//. is much less than 1, and the MAP(3) outperform the MMPP(2), as expected. The proposed MAP(3) well characterizes the cell scale component as well as the burst scale component of superposed traffic streams.

Recently, a number of empirical studies have demonstrated the existence of long-range dependence (LRD) or self-similarity in VBR video traffic. Since previous LRD models cannot capture all short- and long-term correlation and rate-distribution while still retaining mathematical tractability, there exist many doubts on the importance of SRD, LED, and rate-distribution on traffic engineering. In this paper, we present a video traffic model based on the shifting-level (SL) process with an accurate parameter matching algorithm for video traffic. The SL process captures all those key statistics of an empirical video trace. Also, we devised a queueing analysis method of SL/D/1/K, where the system size at every embedded point is quantized into a fixed set of values, thus the name quantization reduction method. This method is different from previous LRD queueing results in that it provides queueing results over all range not just an asymptotic solution. Further, this method provides not only the approximation but also the bounds of the approximation for the system states and thus guarantees the accuracy of the analysis. We found that for most available traces their ACF can be accurately modeled by a compound correlation (SLCC): an exponential function in short range and a hyperbolic function in long range. Comparing the queueing performances with C-DAR(1), the SLCC, and real video traces identify the effects of SRD and LRD in VBR video traffic on queueing performance.

We consider a statistical multiplexer fed by heterogeneous on and off sources. We provide closed-form results on the tail behavior of the queue-length distribution for statistical multiplexers, where the tail behavior can be expressed in terms of traffic parameters such as the first and second moments of on and off periods for individual sources. Since our results are of simple closed-form, they can be used to provide a simple and efficient way to predict the tail behavior and the impact of traffic parameters on performance.