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Bibliographic Information

A control frame is used for controlling access to the medium. In the case that the control frame is not a response frame to another frame, the WLAN device transmits the control frame after performing backoff if the DIFS has elapsed. The type and subtype of a frame may be identified by a type field and a subtype field in a Frame Control FC field. In this case, the AIFC[i] may be used for a data frame, a management frame, or a control frame that is not a response frame. In the example illustrated in FIG. The medium is busy for a time period during which the STA transmits the frame.

During the time period, upon generation of a frame to be transmitted, another STA may defer access by confirming that the medium is busy. If the medium gets idle, the STA that intends to transmit the frame may perform a backoff operation after a predetermined IFS in order to minimize collision with any other STA. Specifically, the STA that intends to transmit the frame selects a random backoff count, waits for a slot time corresponding to the selected random backoff count, and then attempt transmission.

The random backoff count is determined based on a Contention Window CW parameter and the medium is monitored continuously during count-down of backoff slots i. If the backoff slot count reaches 0, the STA may transmit the next frame. Referring FIG. STA 1 may determine whether the channel is busy by carrier sensing. The STA 1 may determine the channel occupation based on an energy level on the channel or correlation of signals in the channel, or may determine the channel occupation by using a Network Allocation Vector NAV timer.

Upon determining that the channel is not in use by other devices during DIFS and after the NAV timer has expired, STA 3 may attempt channel access after a contention window after a random backoff has elapsed. For example, upon receipt of an instruction requesting transmission start from the MAC layer, the PHY layer may switch to a transmission mode, construct a frame with information e. Upon detection of a valid preamble in a received frame, the PHY layer monitors a header of the preamble and transmits an instruction indicating reception start of the PHY layer to the MAC layer. Information is transmitted and received in frames in the WLAN system.

[Teste2] 2nd CfP: ACCESS 2010 || September 20-25, 2010 - Valencia, Spain

The most basic e. The LTF field is used for channel estimation, frequency error estimation, etc. The RATE field may include information about a modulation scheme and coding rate of data. When needed, the Data field may further include padding bits. The padding bits may be used to match the length of the Data filed in predetermined units. The NDP frame format may be referred to as a short frame format. The IEEE It is assumed that frequency and time increase in the upward direction and the right direction, respectively.

In the example of FIG. While the term subchannel is used in the present disclosure, the term subchannel may be referred to as Resource Unit RU or subband. Terms like a bandwidth of a subchannel, a number of tones or subcarriers allocated to a subchannel, a number of data tones or data subcarriers allocated to a subchannel can be used to express a size of a subchannel. A subchannel refers to a frequency band allocated to a STA and a basic subchannel unit refers to a basic unit used to represent the size of a subchannel.

While the size of the basic subchannel unit is 5 MHz in the above example, this is purely exemplary. Thus, the basic subchannel unit may have a size of 2. In FIG. Set to 1. Set to 1 otherwise. Set to 1 if short guard interval is used in the Data field. N SYM is defined in Set to 0 otherwise. BB23 Tail 6 Used to terminate the trellis of the convolutional decoder.

Set to 0. However, the present invention does not exclude non-allocation of a intermediate subchannel of one channel to a STA. A subchannel for each HE STA may be allocated only within one channel, and may not be allocated with partially overlapping between a plurality of channels. This means that one subchannel may not be allocated with crossing a channel boundary. As described above, it is not allowed that one subchannel belongs to two or more MHz channels. Particularly, a 2. In the 2. As illustrated in the lower part of FIG. In the forgoing example of the present invention, the subchannel allocation to STA 4 is not allowed.

As illustrated in the upper part of FIG. In the forgoing example of the present invention, the subchannel allocation to STA 9 is not allowed. On the other hand, it may be allowed to allocate a subchannel partially overlapped between a plurality of channels i. While the following description is given with an assumption that one subchannel has a channel bandwidth of 5 MHz in one channel having a channel bandwidth of 20 MHz, this is provided to simplify the description of the principle of the present invention and thus should not be construed as limiting the present invention.

For example, the bandwidths of a channel and a subchannel may be defined or allocated as values other than the above examples. In addition, a plurality of subchannels in one channel may have the same or different channel widths. According to an example of the present invention, a relationship between a number of total spatial streams transmitted in one subchannel and a number of HE-LTF are listed in [Table 2]. Referring to [Table 2], if one spatial stream is transmitted on one subchannel, at least one HE-LTF needs to be transmitted on the subchannel.

If an even number of spatial streams are transmitted on one subchannel, at least as many HE-LTFs as the number of the spatial streams need to be transmitted. If an odd number of spatial streams greater than one are transmitted on one subchannel, at least as many HE-LTFs as a number of adding 1 to the number of the spatial streams need to be transmitted. PSDU transmission on each subchannel at a different time point results in discrepancy between OFDM symbol timings of subchannels, thereby no orthogonality is maintained.

Or it may be said that the lengths of HE-LTF sections are equal on a plurality of subchannels for all users i. A different number of spatial streams may be allocated to each of a plurality of subchannels, and the number of spatial streams allocated to one subchannel is the number of total spatial streams for all users allocated to the subchannel. That is, the number of HE-LTF symbols may be determined according to the number of spatial streams allocated to a subchannel having a maximum number of spatial streams by comparing the number of total spatial streams for all users allocated to one of a plurality of subchannels with the number of total spatial streams for all users allocated to another subchannel.

P of another subchannel. Therefore, information about the number of spatial streams to be transmitted should be indicated to each HE STA. Accordingly, the STA may determine neither the total number of spatial streams transmitted across a channel nor a maximum number of spatial streams. To solve this problem, a common parameter i. The trigger frame may include a common parameter e.


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For example, each STA may have only to determine the total number of spatial streams, the maximum number of spatial streams, and the number of spatial streams allocated to individual STA, as indicated by the AP, and configure a HE PPDU according to the determined numbers, without including information about the total number of spatial streams or the number of spatial streams allocated to the STA in the HE PPDU.

Common transmission parameters e. In this case, a description of each field given below may be applied only in the presence of the field. This feature may mean that the HE-LTF field start at the same time point and end at the same time point across all users i. Because the padding corresponds to a non-data transmission time period i. First, a plurality of types of paddings according to the present invention will be described in detail with reference to FIG. In the present invention, a plurality of types of paddings may be defined and used.

The plurality of types of paddings include MAC padding, PHY padding, and extension padding and two or more of the padding types may be used. As illustrated in FIG. According to the present invention, MAC padding includes adding a necessary number of padding bits after an MPDU including actual payload.

For example, an MPDU i. For example, a plurality of subchannels allocated within one transmission channel e. A PPDU frame includes a preamble e. The key advantage over MAC protocols which use guard times is that the Guard Bands GBs are not fixed at some arbitrary or maximum level which results in unnecessary power waste.

A further refinement to the algorithm is introduced by using the DAF, which allows GBs to be based on actual drift AD of the respective time bases. This ensures even less waste by keeping GBs as close to the required minimum as possible. The protocol simulations showed that energy efficiencies were identified through nodes remaining synchronized while only waking when absolutely necessary. Fang et al. BodyMAC is based on a downlink and uplink scheme in which the free part of the uplink subframe is completely collision free.

Kundrecensioner

An efficient sleep mode is introduced to reduce the idle listening duration especially for low duty cycles. Simulation results show a superior performance compared to Omeni et al. Once a node has joined the WBAN, collision is prevented within a cluster as all communications are initiated by the central node and addressed uniquely to a slave node. The disadvantage of the protocol is increased complexity at the central node although it is assumed the central node has more power and processing resources.

The concept of a wakeup fallback time is introduced to handle time slot overlaps. Energy efficiency over The control algorithm enables the BSN coordinator to adjust parameters of the DQ-MAC grants immediate access for light traffic loads behaving as a random access mechanism and seamlessly moves to a reservation system for high traffic loads, eliminating collisions for all data transmissions. Schedule-based approaches to node communications within WBANs have the overhead of synchronization, but have the advantage of being collision free, low duty cycle in operation and do not suffer from high levels of overhearing.

Nodes can only transmit data during their assigned time slots, therefore, collisions are avoided. Nodes can turn their radio on for their assigned time slots ensuring that low overhearing and low duty cycle operations can be achieved. TDMA-based protocols can reduce latency by guaranteeing dedicated time slots for each node to send its data. Nodes can achieve synchronization by using the heartbeat rhythm without having to turn on their radio.

This means that the energy cost for time synchronization can be avoided thereby increasing the lifetime of the network dramatically. H-MAC has the obvious limitation of a single point of failure, i. Additionally, results may be affected by patients with a weak heart or those suffering from a cardiovascular condition where some sensor nodes may not be able to detect the synchronization data. Sensor nodes may request varying channel resources under different scenarios. Steady state monitoring, for example EEG or blood glucose transmissions, could yield channel priority to heart rate and ECG sensor data which depending on the criticality of the patient, could be classified as high priority.

Liu et al. The protocol is designed around hybrid frame structure , channel aware adjustment of access mechanisms , and traffic aware adjustment of transmission priority. The protocol incorporates a hybrid approach to channel access using a TDMA and contention-based model to reduce energy consumption and latency. The dynamic adjustment of channel access in CA-MAC can significantly increase the probability of reduced packet loss and ensure successful transmission. Based on traffic requests, sensor nodes with high priority can access the channel faster and transmit more data whereas more steady state low priority traffic is restricted.

This approach means that priority nodes obtain a higher duty cycle and are allocated more slots for data transmission. Lower priority nodes can release available bandwidth or even cease transmission thereby preserving battery life. Al Ameen et al. An additional receiver attached to the sensor node operates independently from the main node radio to reduce idle listening and reduce power consumption at the node level.

The model incorporates periodic and emergency traffic scenarios. WBAN traffic was categorized into normal, emergency and on-demand traffic types. Results showed improvements over Hussain et al. The protocol caters for the scenario where the WBAN differentiates between normal and urgent traffic by the use of two BAN coordinators. Urgent packets are directed to a secondary BAN coordinator when the node doesn't have its own guaranteed time slot GTS.

In a traditional WSN context the network layer has to cater for numerous disparate nodes potentially spread over a wide geographical area. Network layer protocols make use of routing algorithms that use multi-hop to route packets to the destination node. In comparison to WSNs, the bandwidth available to WBANs is limited, likely to be shared with other local ISM band devices and is subject to physical layer attributes such as interference, fading, and attenuation due to the specific characteristics of the human body.

Existing WSN research at the network layer doesn't fully consider the range of heterogeneous nodes within a WBAN and are generally concerned with energy efficient routing via static nodes rather than the extensive body movements in a WBAN. The required routing algorithm complexity within WBANs is low in comparison to large-scale WSNs where nodes are potentially distributed across large-scale areas.

However, the unique factors relating to communicating in and around the human body mean that network layer issues need to form an important part of WBAN protocol design. The standard WBAN architecture of a number of heterogeneous nodes linked to a BCU or sink device often assumes single hop routing where all node communications are transmitted directly to the BCU. Zawowski et al. Results showed that a multi-hop strategy is recommended if the energy for pulse generation and reception is higher than a ten thousandth part of the energy for bit encoding and decoding.

In experiments to evaluate path loss models for human body parts torso, back, arm, leg Reusens et al. Observations in both showed that for nodes furthest away from the sink, there is scope for additional energy saving as these nodes consume the most energy and will die first. However, in the multi-hop scenario, the nodes closest to the sink consumed more energy as these nodes need to forward the data received from nodes further away. Results showed that a smart combination of single and multi-hop routing could yield the optimum energy efficiency. Implanted nodes as part of a WBAN can create a thermal effect due to the properties of RF signal communications in and around the human body.

Specific Absorption Rate SAR is a measure of the rate at which radiation energy is absorbed by tissue per unit weight. Exposure to high levels of SAR could result in tissue damage. Tang et al. Results showed it to be a safer routing solution whilst balancing transmission delay and less network congestion. Least Total Route Temperature LTRT protocol [ 55 ] converts node temperatures into graph weights to generate minimum temperature routes.

Since LTRT aims to send packets with the shortest hop counts, it prevents the entire network temperature from rising quickly. Kamal et al. The clustering of nodes, where energy consumption from communications with the sink is equally divided between each of the nodes in the cluster, has been shown to deliver performance improvements in WSNs and could have potential for WBANs. LEACH introduces data fusion into the routing protocol to reduce the amount of information that is transmitted to the sink to deliver significant improvements when compared to conventional routing protocols.

Qin et al. The protocol however, did not consider the nodes location and distance from other nodes. Transport layer protocols operating in a WBAN need to offer reliable packet delivery from the node to the BCU and in the case of specific sensor queries or emergency sensor data requests, reliable data delivery from BCU to node. Another key function of a transport protocol is the management of congestion in the network.

Efficient control of network congestion can conserve battery life and increase the efficiency of packet delivery. TCPs 3-way handshake process with its end-to-end ACK approach would result in increased delay, increased buffer storage demands at the node level and ultimately poor QoS levels.

Energy Efficiency in Wireless Networking Protocols

UDP, although a connectionless protocol, has no guaranteed levels of reliability and will simply drop packets with no potential for recovery, this would obviously be a serious problem for life signs monitoring via a WBAN. The design of energy efficient transport protocols needs to take into account the diversity of applications, traffic characteristics and resource constraints namely energy and fairness amongst a number of heterogeneous nodes.

Protocols need to provide end-to-end reliability, QoS in an energy efficient way and be evaluated using metrics such as Packet Loss Ratio PLR , latency, and fairness. Therefore, transport protocols should have components for congestion control and loss recovery since these two components have a direct impact on energy efficiency, reliability, and QoS [ 59 ]. CODA is a congestion control protocol that provides local congestion mechanisms to provide both buffer occupancy level and channel load condition to indicate network congestion.

PSFQ provides reliable transport from sink to sensor so called reverse path. PSFQ relies on the pump slowly operation to limit congestion but congestion will occur as the node numbers increase. A design solution involving a combination of CODA and PSFQ could potentially provide both congestion control and reliability in low power sensor networks.

ESRT aims to provide reliability and congestion control with minimum energy usage. Reliability is defined by the number of data packets originated by an event that is successfully received at the sink using the ESRT algorithm.

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The ESRT algorithm tracks the event reporting frequency f of the received packets and matches it with the required reliability metric. Congestion is managed by decreasing reporting frequency without affecting reliability. The application layer for a WBAN includes the application running on the node that may be specific to the sensor type as well as management, security, synchronization, and query type functions. Any application specific QoS constraints, e. At the application layer system administrators can interact with the nodes by using a Sensor Management Protocol SMP [ 63 ].

A SMP enables the lower layers to transparently interface with the application layer to undertake key management tasks such as management of rules relating to attribute naming and clustering, time synchronization and authentication. Compression of data at the application layer is a vital process that consolidates the data contained within each packet therefore, requiring fewer transmissions resulting in energy savings.

Nodes located close to each other may sense values that do not differ significantly. Each node would therefore, encode its data using fewer bits than it ordinarily would, making it impossible to retrieve the measured value with information from only one node. However, when all measurements reach the sink node, the DSC technique can combine the sensors encoded data to retrieve the values measured by all the sensors with minimal coding error. This process effectively moves the computational complexity from node to sink, thus fewer bits are transmitted and energy is saved.

Other techniques such as Data Fusion and Data Aggregation [ 66 ] are further examples of methods used to reduce transmission data and save energy in low power networks. Compressed Sensing CS is a relatively new signal processing technique that holds great promise for leveraging greater efficiency in the compression and recovery of signal data [ 67 ]. CS theory asserts that sufficient signal data can be recovered from far fewer samples or measurements than traditional methods where the sensed data adheres to a number of key criteria.

CS relies on two principles: sparsity —which relates to the signal of interest and incoherence —which relates to the sensing modality [ 68 ]. Efficient sampling and sensing protocols can be designed based on CS techniques to capture useful data content embedded in a sparse signal and then condense the raw data into a reduced data set. What is most remarkable about CS is that it will allow a sensor node to very efficiently capture data in a sparse signal without needing to comprehend that signal, then by using numerical optimization techniques, CS can reconstruct the full length signal from the small amount of collected data.

CS is a very efficient and effective signal acquisition method that in the context of a WBAN, could sample the data from a sensor node at a low rate and later reconstruction from what appears to be an incomplete set of measurements at the sink. The complexity of CS in comparison to standard Nyquist rate based signal processing techniques is moved to the sink side.

This process alleviates complexity and therefore, battery draining processing from the sensing node. CS is an active research area and could hold great potential for WBANs, but careful analysis of the recovered signal must form a vital part of any research to ensure no QoS thresholds are breached and the accuracy of patient life signs data is not compromised. Cross-layer design is the concept of merging two or more layers within the protocol stack to improve the efficiency of the interaction between the protocols. The Open Systems Interconnection OSI model is a protocol stack abstraction that was developed to standardize communications by developing the concept of logical layers.

The protocols at each layer hide the complexity of the layer below and provide services to the layer above. The protocols that fit into this type of model do not need to be aware of other protocols in the layers above or below. This offers many advantages in terms of scalability, compatibility, and flexibility of network design. Resource efficiency can be gained by exploring a more unified scheme that merges common layer protocol functionalities into a cross-layer module for resource constrained nodes.

However this type of structure, whilst possessing many advantages, cannot offer a consistent one size fitting solution for all network design problems. Protocol schemes that move away from the traditional layered model, whilst identifying significant advantages, must counter these improvements in network performance with a balanced view of the potential drawbacks of scalability or compatibility that may be introduced with the implementation of cross-layer solutions.

The interaction between the layers can be varied but the justification to move away from the traditional model must be based on key benefits with a careful assessment of any downsides. There are a number of reasons why the traditional layered approach to network design has been questioned and many of these have direct relevance to the specific needs of WBANs:. The standard layered protocol stack can adequately cater for the requirements of heterogeneous networks such as WBANs in terms of integration into a defined structure, but this may be at the expense of performance and energy efficiency.

For example if a routing path is set up between two nodes through different types of network, the routing protocol can simply find an available path considering metrics as shortest distance or lowest cost. However, if nodes want to find a path with enough bandwidth, then the routing protocol needs to consider the interactions with the MAC layer.

This cross-layer interaction isn't possible via the standard protocol stack. High PDR, low levels of packet transmission delay, minimal collisions and retransmissions, optimal balancing of high energy efficiency and reliable transmission are all areas that are keys within the WBAN environment. The traditional layered structure may not be the optimal solution to guarantee these critical levels of service and may limit the potential improvements needed to guarantee energy efficiency and improvements to QoS. The capacity of a link within a WBAN can vary not just due to the standard wireless link issues such as node interference [ 13 ], but issues due to the inherent behavior of RF signals in and around the human body such as signal absorption and attenuation effectively resulting in a variance in RF transmission power and path losses depending on the direction of propagation.

Channel conditions can change due to factors such as antenna orientation, clothing type, physical stature of the patient, and postural position [ 69 ]. These changes in channel conditions can be catered for specifically within cross-layer schemes that incorporate link adaptation to take account of channel variances. The closely coupled nature of the standard layered protocol stack means that interaction between protocols is standardized but potentially at the expense of performance. Data communication flows from one layer to another regardless of whether the protocol in any particular layer has any significant role to play in the overall transmission or receipt of data.

Most cross-layer schemes involve the communications between different adjacent or non-adjacent layers of the protocol stack to improve the performance in some way over the traditional layered approach. These performance gains can be in the form of energy efficiency, reduced contention, better routing decisions or improved reliability. Research has shown that cross-layer designs can have a beneficial effect on the performance of wireless networks [ 70 — 72 ].

Taking a step back and looking at the protocol stack as a whole can help to focus on new solutions to wireless communication issues that a cross-layer approach can alleviate. Srivastava et al. The main categories studied were: Creation of new interfaces: schemes that connect lower and higher layers either up or down and schemes that create an iterative flow between the two connected layers in both directions.

Merging of adjacent layers : two adjacent layers merge their functionality to create a union of services. Vertical calibration across layers : setting of parameters across the layers either at design or runtime. New abstraction that replaces the protocol stack : disposing of the traditional protocol stack and replacing it with a new method that performs the same functions but in a non-layered form.

Performance gains can be achieved where a higher layer can use a parameter that is available in a lower layer to make better, more informed choices at the higher level. For example a routing algorithm at the network layer could select a route based on a channel condition parameter, e. Lower layers can also be linked to higher layers in a scheme where the information flow is downward through the protocol stack. Here for example, the application layer could directly link with the MAC layer to communicate upon latency requirements as part of an overall QoS requirement, allowing the MAC layer to treat these packets as a priority [ 74 ].

Although there are numerous cross-layer schemes that couple, for example, the MAC and physical layers [ 75 , 76 ], these schemes still retain the traditional stack architecture. Efficiencies can be gained by creating a new super-layer that effectively merges the functions of both layers without the traditional overhead of two entirely separate layers. This union of the two layers services would not require new stack interfaces but rely on the existing interfaces to the rest of the protocol stack. This type of cross-layer interaction involves the adjustment of parameters that span different layers in the protocol stack.

The motivation here is that the potential performance gain at any particular layer is a function of all the parameters of the layers below it. Therefore, joint optimization undertaken in this way can yield increased performance benefits over optimization at the individual layer level.

To enhance throughput, Adaptive Modulation and Coding AMC has been incorporated at the physical layer to match time varying channel conditions to transmission rates. Achieving high reliability at the physical layer however, requires protocols that can reduce transmission rates using either small size constellations or powerful low rate error control codes [ 77 ]. Another way to mitigate channel fading is to utilize ARQ at the MAC layer to improve system throughput and to limit the number of retransmissions.

Lui et al. This method of cross-layer design effectively dispenses with the traditional protocol stack and replaces it with a completely new architecture. Layering as optimization decomposition is a concept that effectively decouples the traditional protocol stack and provides a framework for cross-layer design [ 78 ]. In this method the traditional protocol stack is dispensed with and replaced by a single integrated solution.


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  5. The research by Chiang et al. The theory exposes the interconnections between layers as different ways to modularize and distribute a centralized computation. Separate vertical decompositions functions of an optimization problem in the form of a generalized network utility maximization NUM are mapped to a layer or the interfaces between specific layers. The NUM can take the form of vertical or horizontal decomposition. Vertical decomposition : entails the decoupling of the protocol stack where network protocol functions such as energy detection, congestion management, routing, error control etc are coordinated as part of modules that perform the same functions as the separate layers.

    Horizontal decomposition : can be carried out to further optimize and control the functional layer interaction. The net effect of this is to decompose the optimization problem into sub-problems each associated or mapped to a specific protocol layer with defined functions managing the interfaces between the layers. Chiang et al. However, Layering as Optimization Decomposition does not supersede the need for cross-layer design. The decomposition process involves the development of modules that retain coupling between layers and could be seen as justifying the requirement for cross-layer design [ 79 ].

    The need for cross-layer design solutions is reinforced in cases of architecture mismatch between an existing protocol stack and an optimal decomposition method. Layering as Optimization Decomposition provides a top down approach to designing network architecture from first principles. The resulting conceptual simplicity stands in contrast to the ever increasing complexity of communication networks [ 80 ].

    Although the case for Layering as Optimization Decomposition is still to be fully made in terms of its practical application, it can provide benefits for the modeling of a decomposition scenario in providing a direct comparison to an existing protocol stack identifying which layers to integrate. Cross-layer protocols design specific to WBANs is a relatively immature research area but has the potential to deliver greater efficiencies than single layer adaptation schemes.

    Cross-layer protocol research in the comparable WSN area is more established with many schemes able to demonstrate significant energy efficiency improvements via the optimization of two or more layers. Generally, cross-layer schemes can be divided into loosely coupled and tightly coupled designs. Loosely coupled protocol designs focus on adapting the parameters available at a lower layer to optimize the performance at a higher layer. For example channel conditions at the physical layer could be utilized at the network layer as part of an intelligent routing algorithm.

    In the tightly coupled approach to cross-layer design, the different layers are optimized together to form one complete solution to an optimization problem. Performance gains for tightly coupled designs should be greater than loosely coupled as they do not incur the same stack communication overhead, however this may be at the expense of protocol transparency and maintenance. This section highlights the benefits of cross-layer interaction across specific layers and details some of the relevant cross-layer schemes and the benefits they deliver to low power wireless communications.

    As the physical and MAC layers are close to each other in terms of their protocol stack roles, many cross-layer schemes have adapted both layers as part of a jointly optimized scheme to deliver improvements to traditional protocols. In practice, protocols generally incorporate a closely coupled interaction between the lower parts of the MAC layer and the physical layer. Many physical layer techniques for transmission, modulation and spread methods can enhance performance at the physical layer by improvements in throughput, delay and collision management, but it's only at the MAC layer level that these performance gains can be best adapted and optimized.

    A variety of factors can affect performance in a low power wireless network, such as channel properties, traffic load, energy management policy, etc. The time varying nature of the wireless channel can have a significant influence on node energy consumption where poor link quality can result in increased energy usage. CAEM allows a node to dynamically adjust the data throughput by changing the amount of error protection incorporated by the node according to the current quality of the link, estimated bandwidth and traffic load. The protocol buffers the packet temporarily until the channel recovers to the required quality.

    The obvious overhead is the inherent latency and potential buffer overflow due to the temporary storing of packets. To avoid this the protocol incorporates a scheduling and queuing algorithm to ensure that every sensor can equally access the wireless channel under such a fluctuating environment, thus achieving a balance between energy efficiency and fairness.

    For frequency selective channels, however, the SNR alone does not adequately describe the channel quality. Cross-layer performance can be significantly improved if the link adaptation scheme is based on a more detailed description of the channel condition. An extended exchange of information between the MAC and physical layers is required to fully exploit the status of the current channel conditions [ 82 ].

    Utilizing detailed knowledge of the actual channel condition that is already available at the physical layer as prediction of the packet error probability for the currently observed channel can be obtained and exploited to improve performance. At the physical layer the parameters transmit power, modulation, and coding rate have a direct impact on multiple access of nodes in wireless channels by affecting node interference.

    Kozat et al. QoS can be interpreted differently at each of the protocol layers. At the MAC layer and higher layers, it is normally expressed in terms of minimum rate or maximum delay guarantees. A QoS guarantee that is explicitly based on both minimum rate requirements and maximum tolerable BER is a good compromise, but must be satisfied at minimal energy expenditure. Wang et al. Time slotted and unslotted sleep modes were used in the MAC layer. Energy consumption was expressed by the product of power level and time slot length.

    Simulation results showed that the cross-layer scheme achieved minimal energy consumption, thereby extending node lifetimes, while the spectral efficiency in the whole SNR range was maximized. The network layer is responsible for selecting the optimal routing path for data packets. Different routing decisions alter the set of links to be scheduled and thereby influence the performance of the MAC layer, e.

    When QoS requirements are ignored and link costs that accurately quantify the energy consumption can be assigned, the network layer becomes the sole determinant of energy consumption [ 71 ]. These link costs, however, depend on the transmit power which is a function of decisions made at the MAC and physical layers. In many areas of adaptive MAC protocol design: S-MAC [ 33 ], T-MAC [ 35 ], and DMAC [ 36 ], the research is focused on the adaptation of the MAC layer and ignores the inter-working between different layers thereby attempting to avoid collisions among neighbor nodes without considering any routing information from the network layer or traffic patterns from the application.

    The best routing path can be identified by extracting key information from the lower layers, such as traffic volume, link quality, and collision data, to enhance performance at the network layer [ 84 — 87 ]. It could be argued that integrating routing with MAC as part of a cross-layer jointly optimized solution makes sense as the two functions are very closely coupled and a case can be made for integrating the layers either as one complete module or two closely coupled modules in the same layer.

    If routing is not taken into account by the MAC layer, optimal performance can only be achieved locally [ 80 ]. Cui et al. The proposed scheme incorporated a variable length TDMA protocol where the slot length is optimally assigned depending on the network layer routing requirement while minimizing the energy consumption across the network. CoLaNet [ 89 ] considered characteristics of the application to make better routing path choices at the network layer and demonstrated energy savings over S-MAC. Safwati et al.

    This allows the network layer to choose the route that minimizes the probability of error to achieve the most energy effective route. Most cross-layer designs look at the integration of adjacent or non-adjacent layers to adapt the protocol stack to deliver efficiencies over the traditional stack architecture.

    Schemes that extend the optimizing techniques to layers of intermediate nodes can provide additional energy saving benefits [ 70 ]. The network layer of a source node could be made aware of the channel conditions in the lower layers of the nodes in the neighborhood as part of a multi-hop scenario. Nodes could detect congestion and interference at the MAC layer and immediately react to it at the network layer. Routing decisions could be better addressed as more knowledge about the MAC and physical layers of adjacent nodes is available.

    Ruzzelli et al. The network was divided up into time zones where each one takes turn in the transmission where nodes in the farthest time zone start the transmission. In the next slot the farthest but one sends its data and so on until the sink is reached. The protocol mitigates the hidden node problem, provides configurable shortest path routing to the PAN coordinator and almost doubles node lifetime for high traffic scenarios compared to standard WSN protocols. Any protocol operating at the network layer needs to resolve the inherent conflict between energy efficiency and throughput.

    Sleep Collect and Send Protocol SCSP [ 90 ] dynamically calculates the node sleep and data receive collect periods depending on the amount of incoming traffic. The network layer uses a modified version of ZigBee routing that is more tolerant to node failures. The MAC layer provides the list of neighbor nodes to the network layer, which in turn provides multiple forwarding choices to it. Therefore, the MAC protocol has the option to change to the next hop router during transmission if the message is not successfully transmitted after n number tries. SCSP saves energy consumption by switching between active and sleep periods by dynamically adapting them depending on the amount of received traffic.

    The protocol uses a simple but efficient routing protocol that does not need route maintenance or discovery and works jointly with the MAC layer to enhance its fault tolerance properties. Simulations show that SCSP extends the network lifetime and connectivity in comparison with As the channel quality can vary due to the changing characteristics inherent in the physical layer of a wireless network, resource at the MAC layer is therefore, variable [ 80 ].

    These variations can result in fluctuations of link capacity and transmission since transmission rate is related to many factors, not just link quality. Due to energy constraints and protocol simplicity, some low power standards, e. This means only limited transport layer functions packet fragmentation and re-assembly at the application layer as there is no fragmentation support at the network layer. Typically for traditional wireless networks, the standard protocols operating at the transport layer are TCP— providing connection orientated services to the network , and UDP— providing connectionless services.

    802.11 Frame Analysis

    For example, transmitting IPv6 packets over Additionally, as UDP cannot control traffic rate at the transport layer. The only way the traffic can be managed is via connection admission control or end-to-end rate control. These schemes would need to be cross optimized with the physical layer to cater for the variable link capacity. Standard TCP can manage congestion avoidance, but as it was originally designed for wired networks, it suffers from performance issues related to interpretation of BER, limited bandwidth, and assumptions that packet loss is mainly caused by congestion.

    Performance gains can be made by optimizing a congestion control algorithm utilizing physical layer parameters as part of a cross layer scheme. As the wireless link is prone to varying channel quality, fading, and interference, transport layer protocols can deliver better performance when optimized to consider the varying link capacity [ 91 ]. Cross-layer design solutions operating at the transport and physical layers could, for example, report the channel condition from the physical layer as a new parameter to the transport layer that would enable a protocol to distinguish real congestion from packet loss to make better performance related decisions.

    Spectrum sensing mechanisms operating at the lower layers can mitigate the issues relating to neighbor node interference, allowing protocols to sense the spectrum and access the channel in an opportunistic way allowing the transport layer to make more informed decisions concerning congestion and collisions in delivering reliable communications [ 92 ].


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    • Protocols for High-Efficiency Wireless Networks.

    Although there are numerous examples of cross-layer schemes involving the lower layers, generally, cross-layer solutions incorporating the application layer do not figure highly in the available literature. Many existing protocols operating at the application layer were designed for wired networks and do not perform optimally in the low power wireless context.

    Schemes that can perform application level adaptation based on information from lower layers could provide performance benefits in low power wireless networks. The application layer can communicate the applications' QoS needs, i. Rahman et al.

    High-Efficiency Wi-Fi 6 (IEEE ax) - Accton Technology

    Priority was given to real time data in terms of delay and available link capacity. The scheme linked the QoS requirements at the application layer and the packet waiting time, collision resolution and packet transmission time metrics at the MAC layer. CC-MAC exploits the spatial correlation between nodes to reduce energy consumption without compromising the estimated reliability achieved at the sink. In their work on a new energy saving MAC model, Otal et al. The research incorporates a fuzzy rule scheduler that optimizes the MAC layer to improve overall performance in terms of QoS and energy consumption.

    The protocol considered the node cross-layer constraints such as physical layer signal quality SNR , system waiting time, and residual battery life to allocate slots within a superframe structure. As part of research that focused on the benefits of cross-layer optimization between application and MAC layers, Chatterjea and Havinga [ 97 ] illustrated how two examples of an adaptive MAC could benefit in exchanging information with the application layer.

    To solve the problems of rapidly draining power sources and congestion in the network, the research exploited the high degree of spatial correlation that exists between the readings of adjacent nodes in a densely deployed network by utilizing a distributed and self organizing scheduling algorithm. The scheduling algorithm prevented two adjacent nodes acting as correlating nodes simultaneously and increased the robustness and accuracy of the data by giving every node a chance to act as a correlating node.

    In particular, changes in link quality may lead to a reduction in the efficiency of the algorithm owing to the continuous rearranging of the scheduling scheme. This highlights the need for the upper layers to be adequately insulated from the instability of the lower layers. It seems that you're in Germany. We have a dedicated site for Germany. Authors: Andreadis , Alessandro, Giambene , Giovanni.

    Radio transmissions have opened new frontiers allowing the exchange of information with remote units. From the first applications of telegraphy and radio broadcast, wireless transmissions have obtained a great success with the widespread diffusion of mobile communications. We live in the communication era, where any kind of information must be easy accessible to any user at any time. Mobile communication systems are the technical support that allows the realization of such concepts. With the term mobile communications we embrace a set of technologies for radio transmissions, network protocols, mobile terminals and network elements.

    The widespread diffusion of wireless communications is making national borders irrelevant in the design, delivery and billing of services, thus requiring international coordination of standardization efforts in order to evolve regional systems towards global ones.