Mac protocols in mobile computing

Assume that there exist N k users for service type k supported in the multicell IDMA system, in which each user adopts the same spreading code and coding rate to transmit information. W is the spread-spectrum bandwidth; R i is the data rate of the user i determined only by the spread gain SG; P i and h i represent the transmitted power and the uplink channel gain of the user i , respectively.

The constraints that the transmitted power and the data rate must fulfill are as follows:. To adjust the transmission power of users, we add the general constraints to 6 and Considering the multicell IDMA system, the total interference power including the intracell interference from users I intra , the received power from adjacent cells I inter , and the thermal background noise P N can be calculated as.

According to the interference calculation model, the other-beam interference factor f other , which is defined as the ratio of the interference power received from the other beams I inter to the interference power produced by users in local beam I intra , can be calculated as. As average interference is utilized, the other-beam interference factor f other presented in previous studies [ 14 ] can be seen as a constant 0.

Consequently, with 11 and 12 , we can represent the I total as. Based on the semianalytical SINR evolution technique, MUD efficiency is considered here as the percentage of the intracell interference cancelled by the multiuser detector. Based on 10 and 14 , we can derive the following expression:.

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4. Distributed MAC Protocol to Improve Energy and Channel Efficiency in MANET.

An effective management of rate scheduling depending on the channel quality and the network load situation assigns rate for online users in the cell, and the main rate adjustment is degradation process. However, rate selection strategy is not specified for multiple rates supported in IDMA system. By taking the time-varying property of the satellite mobile communication channel and adaptive transmission technique into account, we can adjust the sending rate dynamically, according to the satellite feedback control and the ARIMI model, to improve the adaptive ability further.

The rate adaptation can be created by the following procedures. When an incoming call arrives to an overloaded cell, the degradation procedure is activated by reducing the service rate of online user in the terrible channel condition. The strategy can ensure different priority levels for different class calls to satisfy well the QoS requirements of various services. Degradation procedure: Calls of the highest priority get the least consideration for the reduction procedure, whereas calls of low priority can be immediately degraded to a lower bit rate in order to maximize the system capacity.

The system assigns the transmission rate, transmitted power, and the only interleaver of the request, to service in the order of voice traffic, video traffic, and background traffic at each frame. When the resources become overloaded at some frames, background traffic which is pretty relaxed about time delay will firstly reduce transmitted power and the transmission rate of ongoing calls in terrible channel quality. Similarly, if the system is still overloaded, video traffic operates in the same way until degradation factor reaches its maximum value or the system can admit an incoming call.

Meanwhile, due to severe restrictions on bit error rate for calls with low priority, the call can be buffered in the system for another access attempt. It not only decreases the blocking probability but also increases the utilization of resource. Considering the fairness among users, it is unbearable to frequently downgrade rate for the ongoing calls. Thus, degradation factor of class i should be lower than allowable degradation limits w i of class i.

The transmission rates for multimedia calls can be adjusted to accommodate more calls while satisfying the minimum signal-to-interference ratio SIR and transmission rate requirement. So the rate adaptation and power allocation mechanisms can work jointly to decide whether the user should be accepted and assigned with resources.

In [ 16 ], the distinct capacity bottleneck in uplink and the one in downlink are considered, respectively, while both uplink CAC based on interference and downlink CAC based on the base station transmitted power UD-CAC are implemented in [ 9 ] at the same time. Although the UD-CAC scheme achieves a nice tradeoff between capacity and stability of the system and maximizes the performance of the system, it does not take the effect of MUD into consideration.

In [ 17 ], the scheme can make accurate estimation of available resource considering the effect of MUD, leading to low outage probability as well as low blocking and dropping probability.

However, most of the existing CAC algorithms ignoring the influence of satellite channel cannot adaptively change with dynamic environment. On this basis, a multiservice call admission control strategy based on channel quality is proposed. The proposed scheme which is conjunct with rate scheduling and buffering strategy can guarantee high power efficiency and throughput for multimedia traffic even in heavy load conditions, illustrating the high efficiency of CBC MUD.

Especially when communication quality of users get worse, system can take into account the quality of service guarantees, interference and channel quality, and so forth to make judgments on whether it is reasonable and feasible to admit new calls and whether to adjust the ongoing calls to increase access opportunity. Here we extend this accurate and effective technique to the estimation of interference level.

The proposed CAC scheme working in conjunction with rate scheduling and buffering strategy is explained in Figure The transmission rates for multimedia calls can be adjusted to accommodate more calls according to different traffic priorities while meeting their minimum signal-to-interference ratio SIR and QoS requirement, only when congestion occurs. Also, the buffering strategy is introduced to hold the call which cannot be admitted at once to increase access opportunity according to different delay characteristics of the traffic.

Further, assume that the required transmitted power of active user n k is S n k. Then, S n k is written as. In order to evaluate the effect of an active user to the system interference, we define the load factor of a single connection as. Based on the above formulas and the effect of CBC MUD, the total intracell interference power from users in home cell can be written as. Based on 11 and 22 , the total interference received in the home cell can be written as. The minimum transmitted power p i N satisfying the i th user demands can be expressed as.

Now the transmitted powerto the i th user is. Similar to the uplink, f other d is defined as the ratio of the total base station transmitted power from adjacent cells to intracells, and the power generated by base station in the home cell is set as its typical value which is 0. When the background noise is ignored, 31 can be written as. Then the orthogonality factor in the downlink direction can be equivalent to f SINR. With the aid of SINR evolution, the downlink load factor for the i th user and the total transmitted power can be accurately and easily estimated as.

The proposed CAC scheme consists of seven stages, explained in Figure Follow those steps according to the priority of different services. If yes, no further operations are performed; if not, start the rate adaptation. Plus one for the user's downgrade factor w i , j and update the current transmission rate and interference factor. Meanwhile, judge whether degradation factor of class i is lower than allowable degradation limits w i. Else, go to Stage 4. But for a new call, determine whether the buffering queue is empty.

If not, go to Stage 5 ; else, decide whether to admit the call according to. In accordance with class priorities in ascending order, the ongoing calls with poor channel quality perform degradation process. When degradation factors of all ongoing users excluding voice services have reached the maximum and 34 still does not valid, then the handoff call will be refused. Similarly, according to class priorities in ascending order, the ongoing calls with poor channel quality perform degradation process. But unlike the processes for handoff call, when degradable rate of every class has been exhausted and 35 still does not valid, then put the new call in cache queue to be detected when the backoff window value decreases to 0.

Stage 7.

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When the call is completed, release all resources and update the available capacity in the system at the same time. When a new call requests the access to the system, test whether the delay queue is empty and when the delay queue is nonempty, enforce buffering strategy. Due to the necessity for satisfying the different requirements of various services for delay time, time-delay counters for multimedia services designed with different threshold values should judge in real time whether the cumulative delay exceeds a threshold.

If so, reject the call; if not, generate a random backoff period. Specific steps are as follows. Stage 1. Stage 2. Stage 3. The initial setting for the current backoff window value is BW now , and reset the backoff window counter. Stage 4. When the backoff window value gradually decreases to 0, check whether the condition 35 is satisfied. If so, the call is accepted; if not, execute a new rate scheduling immediately and check whether the condition 35 is satisfied. If so, the call is also accepted. Otherwise, step to next stage. Stage 5. Check whether time-delay counter of every user exceeds the given threshold.

If satisfied, reject; otherwise, go to next stage. Stage 6. Then, continue to Stage 3. A cell layout is considered, in which mobiles are distributed uniformly. Suppose the uplink and downlink bandwidth are 3. For each cell there are three classes of traffic, that is, the class of conversational, streaming, and interactive. As in [ 18 ], streaming class is modeled as a discrete state, continuous-time Markov process. The interactive traffic is approximately modeled as the Pareto process.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

Further, there are two major types of calls which can arrive at any cell: Since it is more reluctant to block a handoff call than a new call, the handoff calls should be given a higher priority. Based on the multimedia traffic requirements, the traffic characteristics and QoS requirements are defined in Table 1. The paper analyzes several parameters for ease of comparison: We could see that the higher the priority level is, the lower the average blocking probability and the dropping probability are.

Meanwhile, due to rate adaptation and buffering policy, the proposed MAC strategy based on the channel quality greatly reduces the average blocking probability and the dropping probability. Performance of proposed algorithm is obviously much more excellent than the scheme in [ 9 ], which guarantees the priority and fairness between new calls and handoff calls. In order to verify the ability of the proposed scheme to assure the QoS of all users during their whole service time, the schemes are assessed in terms of outage probability.

Figure 14 illustrates the changing of the outage probability with the arriving rate.

As is shown, the outage probability is relevant to the priority of various classes and the arriving rate. What is more, the proposed MAC strategy based on the channel quality adopts the rate degradation to handle blocking problems, which reduce the link load factor and the whole interference. At the same time, buffering strategies can balance the traffic load effectively. The proposed scheme cannot only ensure a low average blocking probability as well as a low dropping probability but also ensure an ideal overflow probability of the IDMA system. Alippi, C.

A novel medium access control (MAC) protocol for ad hoc network - IEEE Conference Publication

Energy management in wireless sensor networks with energy-hungry sensors IEEE Instrumentation and Measurement Magazine 16 23 2-s2. Dietrich, I. Demirkol, I. MAC protocols for wireless sensor networks: Wei, Y. Shwe, H. Energy saving in wireless sensor networks Journal of Communication and Computer 65 20 27 Google Scholar. Ye, W.

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