The SNR requirement is different for different modulation and coding scheme. Suppose all nodes are assigned channels, and node S is the farthest node from its AP among all nodes assigned the same channel.
We place node I at a position that is farthest from node S, but still can make its packet transmission fail at its receiver. The position of node I in Figure 8 is the farthest point from node S. In order to avoid packet collision from hidden terminals, node S should defer its transmission when node I is transmitting.
In other words, if we denote received signal strength of node I measured at node S as , node S should set its carrier sense threshold higher than. Still, most hidden terminals are removed by setting carrier sense threshold to.
We calculate as follows. First, we define a function that estimates distance between sender and receiver based on the received signal strength and also estimate the path loss based on distance. We use the log-distance path loss model to convert between path loss and distance.
The function calculates path loss from distance, and calculates distance from path loss. Note that other path loss models can be used depending on the environment.
In the equations, , , and are constants. The interfering node, node I, is assumed to be placed at a location close enough to corrupt the packet sent from S to AP1. Let us denote the minimum SNR required as. Then, should be large enough to make the following inequality true:. We first calculate and using the following equations:. In the equations, is the path loss between node S and AP1, is the path loss between node I and AP1, and is the transmit power.
We assume that all nodes in the network use the same transmit power. Now, we calculate from and using the following equation:.
In the equation, is a parameter that can be tuned. If is positive, the nodes transmit more aggressively. This could increase the total channel throughput, but could starve some nodes due to hidden terminals. On the other hand, if is negative, the nodes transmit more conservatively. Figure 9 shows the distance between mobile node and AP, and carrier sense threshold calculated from the equations.
Using the relation between distance and carrier sense threshold, we can set the carrier sense threshold of a channel according to distances of nodes assigned to that particular channel. For example, if all nodes are located within 4 meters from their respective APs, the nodes can set the carrier sense threshold to dBm. Figure 10 shows the RSSI of nodes and carrier sense threshold assigned to the nodes, when there are 2, 4, and 8 channels available.
In the graph, we assume that all nodes are high-demand nodes. As shown in the graph, different channels use different carrier sense threshold calculated based on the nodes, and all nodes sharing a common channel are assigned the same carrier sense threshold. With more channels, it is possible to assign higher carrier sense threshold to the nodes, increasing number of concurrent transmissions and improving throughput.
Performance evaluation was done using the ns-3 simulator [ 23 ]. The default network environment is m m area with APs and mobile nodes are deployed. The APs are placed in a grid topology, and mobile nodes are randomly deployed, as illustrated in Figure In default setting, 5 channels are available. The APs can simultaneously access all channels, whereas the mobile nodes can only choose one of the channels. When the simulation begins, the mobile nodes connect to their nearby APs.
This information is gathered at a central coordinator, where mobile nodes are assigned channels according to the algorithm described in Section 4.
Then, the channel assignment is announced back to the nodes. Once the channel assignment is done, nodes start sending traffic. The initial part where information is gathered and channels are assigned is omitted from throughput measurements. However, other channel configurations can also be used without any modifications to the proposed scheme. For most of the simulations, all mobile nodes are high-demand nodes, because they always have traffic to send. In the last experiment, we study behavior of the proposed scheme under dynamic traffic conditions.
For path loss model, we use the log-distance model, which is widely used for indoor environments. For the parameters in the path loss model see 3 , we use the default values from the ns-3 simulator, which are , , and.
The log-distance model calculates path loss of a certain distance based on path loss at a reference distance. In ns-3, the default reference distance is 1 meter, and its path loss is The path loss exponent is chosen depending on the environment, and is often used for office environments with hard partitions [ 25 ]. Transmit power is fixed at 20dBm, and dynamic transmit power is not used. The noise floor is set to The minimum and maximum contention window size are 16 and , respectively.
In order to evaluate performance of the proposed scheme, we have created a multiradio multichannel environment in the ns-3 simulator. The modified structure of modules in ns-3 is described in Figure When a node is sending a packet, the packet is brought down to the interface bonding module from the IP layer.
Specifically, the neighbor table includes a field that indicates which channel the neighbor is using. After looking up the table, the interface bonding module sends the packet to one of the WLAN interfaces in order to transmit the packet. The wireless channel modules are assigned different center frequencies, modeling orthogonal channels defined in the IEEE Each channel module only processes signals that are transmitted on that channel, which means the simulation model assumes there is no interchannel interference between the channels.
In practice, there could be a small amount of interchannel interference even if the channels do not overlap in frequency. Interchannel interference could affect the system performance, and channel assignment algorithm may need to consider interchannel interference when assigning channels to nodes.
We leave this issue as a future work and do not consider interchannel interference in this paper. As discussed in Section 3 , throughput can be increased by letting a small subset of the nodes dominate the channel bandwidth. In the equation, is the throughput of node. We have compared three different schemes. Nodes randomly select channels, and a fixed carrier sense threshold is used. Since DSC does not include an algorithm for channel selection, channels are randomly selected by nodes, similar to the The basic mechanism of selecting the threshold is.
This is similar to 8 , but only considering and not. So compared with Moreover, the carrier sense threshold is different for nodes sharing a common channel, which may result in unfair channel share. Nodes with higher threshold will transmit more often, whereas nodes with lower threshold will tend to defer.
In the simulations, we set and to dBm and dBm. In the graphs, each plot is an average of runs with different network topologies and random number generator seeds.
In the first experiment, we have varied number of nodes from 20 to The result is shown in Figure Intuitively, the node throughput decreases with increasing number of nodes, because the channel bandwidth is shared among the nodes. As shown in Figure 13 a , DSC shows the highest node throughput followed by the proposed scheme and the original When the number of nodes is , the proposed scheme achieves 2. Since all node are using the same MCS level and packet size, the increase in throughput is a result of increased number of concurrent transmissions.
The reason is because different channels use different carrier sense threshold, while the number of nodes is the same for all the channels. Nodes that were assigned to a channel with high carrier sense threshold will achieve higher throughput compared to nodes assigned to a channel with low carrier sense threshold. Compared with Thus, the fairness index can become lower. One possible method to increase fairness is to assign different number of nodes to channels; more nodes are assigned to channels with high carrier sense threshold, and less nodes are assigned to channels with low carrier sense threshold.
This method will increase fairness, but the average node throughput will be decreased, because carrier sense threshold will be set lower compared to when nodes are equally distributed across the channels. Figure 14 shows the sorted node throughput of the three schemes, for a case of nodes. For the proposed scheme, on the other hand, most of the nodes achieve higher throughput compared to In the second experiment, we have varied number of channels from 1 to 9.
For this result, we assume that each channel has a link speed of 54Mbps, and increasing number of channels means using more channel bandwidth. Intuitively, throughput increases as the number of channels increases, because more resource is being used.
However, the efficiency of using more channels is different for each scheme. For With more channels, it is possible for the proposed scheme to assign a more fine-grained carrier sense threshold to channels, as shown in Figure By selecting carrier sense threshold properly, nodes in the channel achieve more throughputs by having more concurrent transmissions.
DSC achieves slightly higher throughput compared to the proposed scheme. In Figure 15 , using larger number of channels meant using more bandwidth to improve throughput. With hardware such as software defined radio, it is possible to divide a single wide-band channel into multiple narrow-band channels, and operate them simultaneously.
Wifi-NC [ 19 ] is one of the examples. When dividing a channel into multiple channels, some bandwidth is lost due to guard band, increased time slot and increased preamble length. For example, IEEE Here we assume that the network interface is capable of dividing a single channel into narrow channels.
We model the data rate of a narrow channel as follows. In the equation, is the data rate of the single wide-band channel, and is the data rate of a narrow channel when the wide-band channel is divided into channels. Then, the data rate of can be calculated as follows:. We assume that the wide-band channel has 54Mbps of link speed, and is 0.
For the proposed scheme, the average node throughput increases with number of channels, but after some point the throughput starts to decrease. However, the proposed scheme makes efficient use of multiple channels by assigning nodes to channels based on their proximity with the APs and selecting carrier sense threshold properly to encourage concurrent transmissions.
When the number of channels becomes large, the capacity loss starts to exceed the benefit of using the proposed scheme, and the node throughput starts to decrease. Up to that point, having less number of contenders benefits the edge nodes. But after some point, this benefit becomes smaller than the capacity loss from dividing the channel, and the throughput starts to decrease.
In the third experiment, we have varied the number of APs from 9 to , while fixing the area size and number of nodes. It is because when the density of APs increases, average distance between a mobile node and its AP is reduced, and higher carrier sense threshold can be used to increase number of concurrent transmissions.
However, In the next experiment, we have varied the size of the simulation area, while keeping the number of APs fixed. Increasing area size while fixing number of APs has similar effects with decreasing number of APs while fixing the area size, because the average distance between mobile nodes and APs becomes longer. The difference is that if we increase the area size, we are also decreasing the node density.
We have varied the area size from 1, to , Note that the default area size was 10, in the previous experiments. The result is in Figure When the area size is increased, the average node throughput of This is because with fixed carrier sense threshold, nodes can transmit more concurrently when they are far away from each other. However, for DSC and the proposed scheme, node density does not have significant impact on the throughput, because carrier sense threshold is adaptively tuned according to the topology.
When the distance between mobile nodes and APs is large, the nodes set their carrier sense threshold to a low value, and so the carrier sense range becomes large. When the distance between mobile nodes and APs is small, the carrier sense range also becomes small. Thus, the amount of spatial reuse stays similar. The carrier sense threshold assigned by the proposed scheme depending on the area size is shown in Figure This is because when the area becomes very large, the fixed carrier sense threshold of dBm is not low enough to prevent hidden terminals, and starvation begins to occur.
The fairness index of The proposed scheme, although it shows slightly less throughput compared to DSC, achieves much higher fairness compared to DSC. When the area size is large, the fairness of In the proposed scheme, the carrier sense threshold of a channel was determined by the mobile node that is farthest from its AP.
This is a conservative approach, because the threshold is calculated so that a single node cannot become a hidden terminal to another mobile node even in the worst case. In practice, it is rare to have nodes positioned exactly as in Figure 8.
So it might be beneficial to increase carrier sense threshold and allow nodes to transmit more aggressively. On the other hand, the calculated carrier sense threshold is not enough to prevent hidden terminals completely, because multiple nodes outside the carrier sense range could harm the transmitter by transmitting signals together. In this experiment, we have varied the carrier sense threshold offset, which is denoted as in Equation 8. Intuitively, the total throughput increases with , because high carrier sense threshold leads to aggressive transmissions.
As discussed earlier, high carrier sense threshold causes hidden terminal problem that leads to severe unfairness in resource share. In the Figure, the throughput starts to drop when is 1dB.
This means that the carrier sense threshold can be adjusted to be slightly higher than what is calculated. Increasing further could result in starvation of some mobile nodes.
When calculating the carrier sense threshold, the proposed scheme relies on a path loss model. In the previous evaluations, we have used the same path loss model and parameters for the algorithm and the simulated environment, which is the best case. However, in practice, there is always mismatch between a model and the real path loss. This mismatch will affect the performance either by creating hidden terminals or exposed terminals, depending on whether the actual path loss is higher or lower than the path loss calculated by the model.
In order to see the impact of the model error, we have conducted an experiment where we vary the path loss exponent of the log-distance model. The path loss exponent is typically set according to the environment based on empirical measurements, such as for infinite space, for office with hard partitions, for office with soft partitions, and so on [ 25 ]. In this experiment, we vary from 2 to 4, which covers most of the environments.
While we vary the parameter, the distance calculation is always done assuming , creating a mismatch between model and the real environment. Figure 21 shows the result. This unfairness comes from hidden terminals as previously discussed in Section 3. Nevertheless, we can observe that compared with In order to avoid starvation at some nodes, we can set the threshold offset conservatively in order to compensate for model error.
When the proposed scheme assigns channels to mobile nodes, it considers traffic demand of the nodes as described in Section 4. In the previous experiments, all mobile nodes always had traffic to send, so all nodes were high-demand nodes.
In order to study the performance of the proposed scheme under dynamic traffic conditions, we conducted an experiment where mobile nodes generate traffic in an on-off pattern. Specifically, each node sends traffic for 60 seconds, then stops sending traffic for 60 seconds, and then starts sending traffic again. The starting time of this traffic pattern is different for each node. The channel assignment period is 30 seconds, and the high traffic demand threshold is set to 0.
We ran simulations with three different schemes, the original We have measured average node throughput every 5 seconds, while running the simulation for 10 minutes of simulation time. The result shows that the proposed scheme achieves higher throughput compared to Also, it can be observed that channel assignment considering traffic demand achieves higher throughput under dynamically changing traffic conditions, compared to channel assignment without considering traffic demand.
If traffic demand is not considered, bandwidth of some channels could be under-utilized, degrading the throughput. Also, the carrier sense threshold may not be optimal for the channel because calculation of the threshold is based on wrong information. Nodes with no traffic should not be included in the calculation.
Classifying nodes into high-demand and low-demand nodes could improve system performance by avoiding channel under-utilization and calculating carrier sense threshold more accurately.
In summary, the proposed scheme achieves higher throughput without causing starvation at the edge nodes. The benefit becomes larger when density of APs and mobile nodes become higher. The proposed scheme benefits from having more channels, but cautions should be taken if we are dividing a single channel to multiple narrow channels, because capacity loss could nullify the benefit of the proposed scheme.
The mismatch of path loss between a model and the real environment could affect the performance, degrading throughput or fairness of the nodes. But it could be compensated by carrier sense threshold offset, which is a tuning knob for controlling the trade-off between throughput and fairness. As the density of wireless LAN increases, it is important to make efficient use of the channel resource. The medium access control protocol of current wireless LAN uses carrier sensing based random backoff mechanism to avoid packet collisions, but the protocol suffers from hidden terminals and exposed terminals especially when the network becomes dense.
Hidden terminals are created by a high carrier sense threshold, whereas exposed terminals are created by a low carrier sense threshold. In this paper, we propose a simple scheme that can improve system throughput in considerable amount, while avoiding starvation at the edge nodes. Using multiple channels, we assign nodes to channels based on estimated distance between mobile node and APs.
Then, carrier sense threshold of each channel is calculated in order to allow as many concurrent transmissions as possible while avoiding the hidden terminal problem. The simulation results show that the proposed scheme works well in various environments and parameter values, compared to the basic It is important to note that there are many issues that were not considered in this paper.
First of all, we assumed that all nodes use the same transmit power. Adjusting transmit power along with carrier sense threshold may further improve the spectrum efficiency. Second, as mentioned earlier, we assumed that the channels are truly orthogonal and there is no interchannel interference between channels.
In reality, interchannel interference exists which can affect the performance. Channel assignment may need to consider the interference in order to prevent performance degradation. Third, we assumed that all APs are capable of accessing all available channels, which may not be true. Some APs may be equipped with less number of radios compared to the number of available channels.
Also, mobile nodes may be equipped with multiple radios, which could be used to improve the performance. Finally, we only considered single-hop wireless LANs, but this idea could be applied to multihop networks such as mesh networks. Then, the channel assignment and carrier sense threshold should be combined together with routing algorithms in order to maximize the performance. All of these issues are directions for future research.
Also, we plan to implement the proposed scheme in a SDR testbed and evaluate its performance, in order to find out any real-world issues that were not present in the simulation study, and further improve the technique.
The data used to support the findings of this study are available from the corresponding author upon request. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Academic Editor: Lin Chen. Received 14 Jan Revised 16 Mar Accepted 14 Apr Published 30 Apr Abstract As the density of wireless LANs increases, performance degradation caused by hidden terminals and exposed terminals becomes significant.
Introduction IEEE Figure 1. An example network environment with 16 APs and 64 mobile stations. The number in each room represents channel used by the AP. Figure 2. Figure 3. Figure 4. Figure 5. Relation between distance to AP and node throughput. Mobile nodes closer to the AP typically get more share of the channel bandwidth. Figure 6. An example scenario illustrating the cause of throughput unfairness between nodes. Upon failure, D increases its contention window, lowering its share of channel bandwidth.
Figure 7. An example channel assignment scenario. High-demand nodes are indicated by the backlogged queue. There are 3 channels and 9 high-demand nodes, so 3 nodes are assigned to each channel. The low-demand nodes are assigned channels according to their RSSI values. Figure 8. An example scenario describing how carrier sense threshold should be decided. Figure 9. Carrier sense threshold calculated based on distance between mobile node and AP. Figure Carrier sense threshold assigned to nodes.
Default network topology. Ns-3 implementation of multiradio network interface for evaluating the proposed scheme. Throughput and fairness varying number of channels. Each channel has a link speed of 54Mbps. Throughput varying number of channels.
In this graph, we assume that channels are created by dividing a single channel which has 54Mbps of link speed. Carrier sense threshold assigned to channels varying area size. Sorted node throughput varying path loss exponent of the log-distance model. Average node throughput over time with dynamically changing traffic. References M.
Borgo, A. Zanella, P. Bisaglia, and S. View at: Google Scholar B. View at: Google Scholar J. Zhu, X. Guo, L.
Yang, W. Conner, S. Wiki User. The FORK system call allows a program to create multiple activities in the same program that run simultaneously. Voice call is free over multiple users but video calling is not free on conference call, as it allows only a single user to continue video but others go off.
A multiple number is a multiple when you times it by something. This is what you call a multiple. Call your provider and ask which channels you get that are this. They will tell you also on a channel guide. You may also be able to just browse through your own channels already and see. A Call Centre refers to a centre that specifically handles 'Calls' i. Telephone based traffic, as opposed to a contact centre which handles 'contacts' from multiple channels i.
Web, Email, Webchat, Click to call, as well as Telephone contact. Go4Customer deals in both. The technology that joins multiple users together on one call is called a conference call bridge. It is beneficial to use this conference call bridge technology because it manages connections and allows for free flow of information among the participants.
The Chass Port of Call clock is a popular attractive design which allows the setting of multiple time zones for display at the same time. Call your cable company, they control which channels you get. No - unless you call empty space the "medium". Many channels are included in the discount television package in Hamilton, Ontario.
To get a full list of channels either browse through them one-by-one or call your television provider. You have to call you can find it in disneys channels in TV. This varies from Cable TV companies so it is hard to say. The local channels are usually the lower number channels.
Call your Cable television company and ask if they have a website to download their channel guide. A multiple birth of nine is called nonuplets. Derive the object from multiple classes. A medium or mystic. Log in. Computer Networking. Study now. See Answer. Best Answer. Study guides. Computer Networking 20 cards. What are advantages of Database Approach. What is a network that covers a large geographical area such as a city country or world.
What is the worlds largest wan. What is a network server. How do you connect to a secured wireless network. What service translates domain names computer hostnames to IP addresses. When was the first commercial computers sold. Business and Industry 22 cards.
What is a network.
0コメント