JP4629065B2 - Device for selecting beamform direction - Google Patents

Description

  The present invention relates to an antenna array beamform.

  The use of beam antennas has proven to be a promising technology for wireless devices. A mobile device with a beam antenna can select the direction of its beam pattern in a wireless network, which can positively affect network connectivity and stability. The beam direction refers to the directivity of the antenna pattern, but the pattern can have any shape determined by the antenna array. Beamform can be applied to radio access networks, mesh networks, vehicle networks and sensor networks, among others.

In general, there are two well-known approaches to beamforming:
a) Random Direction Beamforming (RDB)
b) Communication-based beamforming

  The first solution (approach a) is simple with reduced overhead, but its performance remains limited. RDB (see, for example, Non-Patent Document 1) is a simple method that consists of directing (and fixing) the beam of a directional antenna in a random direction. RDB shows a significant improvement compared to using omni-directional antennas. However, this approach is illustrated in FIG. 1 where nodes close to the network boundary or adjacent to obstacles (showing the case where nodes x and y are directing the beam in a direction with no nodes nearby). As described above, there is a limit when beamforming in a direction in which no neighboring nodes exist. Such nodes are isolated from the rest of the network.

  The second solution (approach b), which uses a communication-based beamform, greatly improves system performance but increases complexity. For details of this approach, see, for example, Non-Patent Document 2. This approach involves selecting the beam direction based on the routing information. In communication-based beamforms, nodes are forced to continuously search for and adapt to their communication partner's location. At this time, tight adjustment between nodes is required, resulting in increased complexity and overhead. This means that the beamform mechanism and the routing mechanism interact and are not independent of each other. The beamform mechanism requires routing information such as the ID and location of the node's peer (or at least the next hop), which increases the overall system complexity. Each node must know the angle at which it can reach each communication partner. This angle is obtained by using an angle-of-arrival estimation or information on the position of each node and the position of their nearest communication partner (adjacent hop). This means that the (OSI) layer responsible for routing and the layer responsible for the beamform (for example, the MAC layer) must interact with each other and exchange information and be interdependent. This situation is undesirable in terms of the overall complexity of the beamform mechanism. Furthermore, since modification is required at two different layers of the ISO-OSI model, it becomes difficult to implement the existing network infrastructure.

C. Bettsetter, C.I. Hartmann and C.M. Moser, “How does randomized improving the connectivity of ad hoc networks?”, In Proc. IEEE Intern. Conf. on Communications (ICC), Seoul, Korea, May 16-20, 2005. R. Roy Chudhhury, X. Yang, R.A. Ramanathan and N.M. H. Vaidya, “Using directional antenna for medium access control in ad hoc networks”, in ACM MobileCom 2002

  In view of the above, an object of the present invention is to greatly improve RDB without requiring the complexity of “communication-based beamform”.

  According to one embodiment, an apparatus for selecting a beamform direction of a node in an ad hoc network, wherein the control module changes a beam angle in each step and controls a beamform direction of an antenna connected to the apparatus; A receiving module that overhears an ongoing transmission and extracts one or more parameters indicating transmission overheared at different angle steps, the control module calculating a decision parameter for each angle step An apparatus is provided that compares the determination parameters of the different angle steps and selects an angle corresponding to an optimal determination parameter as a beamform direction of the antenna based on the comparison result.

  According to this embodiment, a beamform antenna can be introduced in the wireless network to improve routing robustness and connectivity and reduce mutual interference.

  According to one embodiment, the neighbor parameters are sent by other nodes even if there is no specific request from the node that selects the beamform angle, and are obtained from multiple nodes at different angles. The proximity parameter is considered together with a weight when calculating the determination parameter, and this weight is independent of the current or future communication partner of the node that selects the beamform direction.

  This means that the selection mechanism can be based on “passively” overhearing ongoing communications rather than active requests that would include additional communications. Further, rather than relying on the node's current or future communication partner (ie, adjacent hops) for the selection, the selection is based on the entire neighborhood reflected by parameters derived from overheard transmissions. By doing so, frequent changes in angle in the case of communication-based beamforms that take into account any changes in the communication partner can be avoided, as well as cascading effects that can arise from such changes.

  According to one embodiment, the proximity parameter is included in a data transmission or dedicated beacon message at a layer different from or below the layer where the routing protocol operates.

  This has the advantage that beamform direction selection is independent of the routing protocol, and as a result, the complexity caused by the interdependence between beamform and routing can be avoided in the case of communication-based beamform approaches. Has an effect.

  Specifically, the approach based on this embodiment is much less complex than a “communication-based beamform” because it does not require coordination between nodes, and a random directional beam with similar complexity. Significantly surpasses the form approach.

  In this way, the method improves network connectivity, shortens paths (and thus reduces end-to-end delay), reduces interference, reduces mobile device battery consumption, and network capacity. Increase.

  According to one embodiment, the neighborhood parameters are transmitted by the node at regular intervals, and the neighborhood parameters include the number of neighbor nodes, battery level, convergence level, channel quality, When one or more of relative or absolute positions are included and two or more neighboring parameters are considered, a cumulative determination parameter for each angle is determined based on the plurality of neighboring parameters. Calculated.

  Thereby, the node can calculate the optimum beam direction using information about the neighborhood obtained from the parameters, for example, the number of neighboring nodes, their energy level, channel quality, convergence level, position, and the like.

  According to one embodiment, the control module sweeps neighboring nodes by changing the beam direction by a predetermined angle, transmission of data packets by neighboring nodes, and neighbors when a beacon message is used. Overhearing the beacon transmission by the node, maintaining each angle direction for a predetermined time before moving to the next angle, and all received related neighborhood parameters p_k (k = 1,... Based on a set P of status parameters including m), a step of constructing a determination parameter F (P), and F (P) is increased by a certain beam direction, and is larger than a threshold value that exceeds the previous value. In some cases, use a new beam direction and at regular intervals or manual trigger And repeating the above steps based on the above.

  In this way, the beamform selection algorithm can be executed. Regular iteration ensures that the algorithm adapts to changes in network conditions. In addition, for example, a user or operator can provide the possibility of manually triggering beamform direction selection if he believes that the network may be unstable.

  According to one embodiment, the control module includes a step size for incrementing an angle during a sweep and a step time at an angle to obtain a statistically significant sample of status updates in the corresponding direction. Adapt either or both.

  This improves the reliability and efficiency of the beamform selection algorithm.

  According to one embodiment, the information about the neighborhood is sent by the node piggybacked on normal traffic or sent using a dedicated beacon message to send the information about the neighborhood .

  According to one embodiment, the apparatus is a module that changes a threshold applied to determine whether a change in the decision parameter is sufficient to change a beamform direction, wherein the network is A module that increases the threshold if it is detected to be unstable and / or decreases the threshold if it is detected that the network is very stable. This allows the device to adapt to the stability conditions of the entire network.

  According to an embodiment, the apparatus receives the neighbor parameter from a neighboring node at a distance of hop number 1, and based on the neighbor parameter received from a neighboring node at a distance of hop number 1, Calculate judgment parameters.

  This makes it relatively easy to incorporate this mechanism into an existing network structure without significant modifications to individual nodes. This is because each node transmits a parameter (for example, a MAC address) that can be used as a neighborhood parameter to some extent.

  According to an embodiment, the apparatus receives the neighbor parameter from a neighbor node having a hop count of 2 or more, and receives from a neighbor node including a neighbor node having a hop count of 2 or more. Calculating the determination parameter based on the proximity parameter. This improves the connectivity of the entire network and reduces the tendency to form clusters.

  According to one embodiment, the apparatus determines the determination parameter based on a maximum number of neighboring nodes detected at a certain angle.

  This is a relatively easy way to determine metrics for calculating decision parameters that yield reasonably good results.

  According to an embodiment, a network comprising a plurality of nodes comprising the device according to any one of claims 1 to 14, comprising a sensor network, a vehicle network, a wireless mesh network, a radio access network, A network that is any of the above is provided.

  According to one embodiment, the apparatus comprises a module that randomly selects the timing of the first beamform selection performed by a node and selects the timing of subsequent beamform selections at regular intervals.

  This avoids simultaneous execution of many beamform direction selections that can negatively impact network stability.

  According to one embodiment, the regular interval varies according to a random parameter chosen by the module.

  This allows the selection to be performed regularly in order to adapt continuously to changes in the situation, and by introducing random elements, selection clustering at a certain time or period can be avoided.

  According to one embodiment, the selection is performed in a certain order. This ensures that the two nodes do not perform beamform direction selection at the same time. However, this requires some adjustment between the nodes.

  Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings.

  According to the first embodiment, a beamform method and a beamformer with improved performance compared to RDB while avoiding the complexity of communication-based beamforms are provided. According to one embodiment, the choice of beamform direction is based on aggregate information collected from neighboring nodes.

  In this embodiment, some information is obtained without requiring any other node's cooperation at each node (for example, by overhearing ongoing transmissions and estimating the number of neighboring nodes in each beam direction). Can be collected. Information about the number of neighboring nodes is obtained by identifying the number of different MAC (Media Access Control) addresses that can be found from overheard transmissions. This information (a MAC address that is a unique identifier assigned to most network devices) is typically included as a source in a data stream transmitted from a node, and thus identifies the number of different MAC addresses. Thus, the number of nodes can be identified. The control mechanism allows the antenna beam to sweep when the angle is incremented. The angle at which the maximum number of nodes is found can be chosen as the antenna beam direction.

  This means the following. According to one embodiment. As schematically shown in FIG. 2, a receiving module 210 connected to the antenna 200 and overhearing data transmitted from other nodes while incrementing the angle, and the beam direction of the antenna through the control signal 230 are shown. Sweep at different angles (with incrementing steps), extract neighborhood parameters (which are MAC addresses according to one embodiment) from the overheared data stream for each angle, and then based on those neighborhood parameters And a control module 220 for calculating a determination parameter for each angle. Based on the comparison of decision parameters for different angles, the control module 220 selects an angle as the beamform direction of the antenna. According to one embodiment, this is the angle where the maximum number of nodes is found, ie the angle where the most different MAC addresses are found.

  According to one embodiment, the receiving module and the control module can be implemented by a digital signal processor suitably programmed to function as described above.

  FIG. 3 shows a block diagram of a node and its operation as a further embodiment of the present invention. In optimizing the beam direction, the transceiver collects overheared data and a neighborhood parameter p_k (transmitted periodically). These parameters (p_k) are used by a “beam direction calculation” module that controls the beam direction of the antenna. These are collected using the current beam pattern without estimating the angle of arrival. In normal operation, each node periodically includes its own status parameter p_i in a beacon message, or piggybacks on a data packet for transmission.

  The node shown in FIG. 3 also transmits its own internal parameter p_i. The internal parameter p_i is then received as a “neighbor parameter” p_k by another node, thereby affecting the selection of the beamform direction at the other node. According to one embodiment, the proximity parameters are transmitted at the data link layer, or in particular at the MAC layer, which is a sublayer of the data link layer. In FIG. 3, this is indicated by the element labeled MAC. As shown in FIG. 3, data is passed from the MAC layer to the upper layer. However, the neighborhood parameter p_k is not passed to the upper layer. This is because they are transmitted at the MAC layer and are therefore already extracted from the data stream at this level. Similarly, the internal parameter p_i is provided for data streams transmitted at the MAC layer level.

  The transmission of neighborhood parameters in the MAC layer has the advantage that the whole beamform direction selection process can be performed in a layer below, for example, a layer related to the routing algorithm. This means that beamform angle selection can be performed independently of the routing algorithm, thus avoiding the complexity introduced by interdependencies between routing and beamform in communication-based beamforms. Means.

  According to one embodiment, the beamform direction selection mechanism functions independently of any information about the communication partner of the node that selects the beamform. This means that the node that selects the beamform does not consider its current communication partner, such as its current neighbor hop in an ongoing communication session. In other words, it only performs “passive” monitoring of its neighbors by overhearing ongoing transmissions at different angles. This means that routing information such as neighbor hops and neighbor hop location or direction does not affect the beamform direction selection decision and is independent of its own communication intent or state. Instead, without considering its own communication state and requirements, the node scans the neighborhood for ongoing traffic and without taking into account parameters reflecting its own situation and intent regarding its peers, From there, parameters that collectively indicate the neighborhood (cumulative neighborhood parameters) are determined. If any information from a node's current or intended communication partner is considered, these are only considered equivalent to information from other nodes in the same angle step. That is, there is no priority for any node that overhears the communication. In this way, a node is concerned with its own situation with respect to its own communication requirements (for example, "determining where its next hop is and which angle in the front or back direction of the current or intended communication path"). It does not require extensive communication with other nodes to obtain certain parameters. The node does not actively "request" this information, but obtains it by "passively" overhearing. This can be accomplished by scanning “passively” ongoing transmissions and extracting the neighborhood parameters included in these transmissions. Neighbor parameters are transmitted at regular intervals by neighboring nodes without explicit requests, for example using a piggyback mechanism or a beacon signal.

  According to one embodiment, nodes may include status parameters in their beacons, such as their own energy level, the number of neighboring nodes they have, or piggyback into data packets. This information is later received as “neighbor parameters” by other nodes and can be used in one embodiment to determine or calculate decision parameters. This can improve beamform direction selection. The more information about the network that a node has (or neighboring nodes that are at a distance of 1, 2 or n hops), the greater the node will gain by directing beam antennas based on it. However, when not only information about a node itself (internal parameter p_i) but also information about a neighboring node of the node is transmitted, complexity and overhead cost increase. This is because if a node includes not only its own status information p_i but also information about its neighbors in the transmitted data traffic or beacon message, such information must flow through the network via multiple hops. Because it must.

According to one embodiment, the status parameter p_i is
• Number of nearby nodes • Battery level • Channel quality (signal to noise ratio)
・ Congestion level ・ Position (relative or absolute position)
May include one or more of the others.

  According to one embodiment, this information is transmitted periodically at regular intervals, eg, period T_b, without affecting the beam direction of the node transmitting them (ie, the beacon is set to the current beam). Sent by).

  The number of neighboring nodes can be taken into account by selecting the angle at which the maximum number of neighboring nodes is found, as already mentioned.

  The battery level can be taken into account by choosing the angle that increases the battery life of the node, in other words, the angle that maximizes the cumulative energy level. This has the effect of increasing the stability of the network. This is because, at an angle where one node or another node becomes inoperable due to low energy, many communication paths do not exist, and a new path needs to be selected.

  According to one embodiment, nodes may be weighted based on their congestion level, and based on that, cumulative congestion parameters can be determined for different angles. At this time, it is possible to select an angle with a low conversation level.

  The location can be considered to try to cover the area as much as possible without leaving any “white spots” (places where it is difficult for new incoming nodes to find nodes to connect to). It is therefore necessary for the nodes to determine and transmit their absolute or relative position and extract this information from the traffic overheard by the node that determines the beamform angle.

  According to one embodiment, two or more neighboring parameters can be considered when determining the decision parameters for different angles. This can be performed, for example, by determining individual determination parameters based on each neighboring parameter to be considered and calculating the accumulated determination parameters based on the individual determination parameters. In such a case, different weights can be assigned to different individual determination parameters. For example, if there is a particular interest in energy, a higher weight than the number of neighboring nodes, for example, can be assigned to individual decision parameters based on the battery level.

  According to one embodiment, a plurality of different neighborhood parameters are not used to individually determine different decision parameters to be combined later, but the final decision parameters are obtained directly from the different neighborhood parameters.

  Next, an algorithm for selecting a beamform angle according to an embodiment of the present invention will be described in more detail. This algorithm is executed by each node in the network.

  Each node executes an algorithm (algorithm 1) for (re) calculating the beam direction independently of the other nodes. FIG. 4 shows an example of pseudo code for executing this algorithm according to an embodiment of the present invention. Each node starts a nearby sweep by changing the angle of the beam direction in steps of angle_step. For each angle step, each node overhears the data packet transmitted from its respective neighboring node and the beacon if a beacon is used. Each angle direction holds the beam direction only for time_step before the node moves to the next angle step. Next, the node constructs a set P of status parameters including all received neighborhood parameters p_k (k = 1,..., M). The sweepin group searches for a beam direction that maximizes the determination parameter F (P). Here, F () combines all related parameters p_k (battery level, SNR, number of neighboring nodes, etc.). If the new beam direction results in a significant increase in F () compared to the previous one (beyond the threshold), the new beam direction is retained. This search algorithm is iterated at every search_period_duration.

  In this case, these changes must be taken into account in the calculation of F (P) (avg_step as the average of every individual time step, eg by dividing the calculated value by a factor (time_step or avg_step)). Don't be.

  The temporal average number of status updates (done through piggyback or dedicated beacons) determines the speed at which sweeping to calculate the beam direction occurs. If data packets are sent very frequently, it may be sufficient to piggyback status information to some of them. In contrast, if there is very little or no traffic, estimating an accurate image without using a dedicated beacon message takes too much time. Take it. The frequency of beacons can be adapted so that the total number of updates that a node can overhear at each time step is relatively constant.

  According to one embodiment, a threshold parameter can be used to determine whether a change in the decision parameter or optimal value opt_value can be considered large enough to actually change the beam direction. As the threshold is reduced, the beam direction approaches the optimal direction. On the other hand, frequent changes in beam direction affect the stability of the network. When the beam direction is changed, the parameter values of neighboring nodes change, and as a result, the beam direction can be changed. In this case, the wireless routing protocol that is implemented in addition to the proposed beamform protocol has to adapt frequently to neighborhood changes, such as calculating new routes and discarding invalid old routes. . Therefore, it is desirable to adapt the threshold parameter to routing protocol responses, network requirements for energy consumption, availability of alternative paths, etc.

  Intelligent adjustments can be made through further signaling between the beam direction protocol and higher layers (eg, routing layer or even application layer). If the upper layer detects that the network is too unstable, it can change the threshold (and other parameters of the algorithm). This can be detected, for example, by measuring the average connection duration. If this is considered too short, the network can be considered too unstable. Another possibility is to measure the number of times a connection is interrupted within a certain time. If the number is too large, the network can be considered unstable.

  On the other hand, if the network is very stable, the threshold can be reduced. A similar mechanism for measuring network stability can be applied in this case.

  Next, the beamforming technology according to one embodiment will be described in more detail.

  In this embodiment, the mobile terminal initially beamforms in a random direction. Each node then sweeps the main lobe by incrementing the beamform angle by a predetermined amount. When the sweep is complete, the node beamforms in the direction where the node degree is maximum (ie, the maximum number of neighboring nodes is found). When the maximum node order occurs in two or more directions, one direction is randomly selected from these directions. This process is repeated periodically to take into account possible network topology changes.

  In this case, F (P) corresponds to the number of different MAC source addresses overheard for each step of the sweep phase. In the following description, this mechanism is referred to as maximum node degree beamforming (MNDB).

  Next, a beamforming technique according to a further embodiment will be described in more detail.

  In some non-homogeneous topologies, the MNDB may result in sub-optimal connectivity. In this case, the nodes form a strongly connected cluster in each cluster and direct the beam so that there is almost no connection between different clusters. The reason for this situation is that nodes tend to direct the beam so that they can reach the maximum number of neighboring nodes “directly”. Here, “directly” means that there is no intermediate hop. However, as can be seen from FIG. 5A which shows a situation where node X can reach the maximum number of hops directly by directing its beam to cluster A, this is the best solution in all cases. is not. However, in terms of overall connectivity, it may be advantageous if node X directs the beam to cluster B. This is because a connection can be established between these two clusters, and as a result, the overall connectivity can be improved.

  In order to solve this problem, according to one embodiment, as will be clarified below, a node is a two-hop node to maximize the number of different neighboring nodes at a distance of hop number 1 and hop number 2. The order-beam form (TNDB) algorithm can be used.

  In the present embodiment, a node not only transmits its own MAC address as status information or neighbor information, but additionally transmits a MAC address of a neighboring node adjacent to the hop. It will be appreciated that this may require some modifications to the protocol at the MAC layer. This is because its own MAC address is normally transmitted together with arbitrary communication data, but the MAC address of a neighboring node adjacent to one hop is not usually included. However, this can be done by holding the received MAC addresses along with the received data and then resending them in the transmitted data stream as neighborhood parameters. Any node that receives these neighbor parameters uses all of these MAC addresses (the MAC address of the transmission source node and the MAC address of the neighbor node) as input parameters for calculating the determination parameter F (P).

  In such a case, the individual status update information p_k includes a list of MAC source addresses overheared by the node k, and F (P) can add up to 2 hops by summing p_k and removing duplicate MAC addresses. Calculate the number of different MAC addresses of neighboring nodes at a distance. Applying this mechanism to the situation shown in FIG. 5B reveals that cluster B has an advantage over cluster A in this case. This is because it includes a larger number of reachable nodes through a two-hop connection, and accordingly node X directs the beam to cluster B.

  Using TNDB as shown in FIG. 5B, node X is connected to a neighboring node in cluster A through a side lobe and uses the main lobe to reach a neighboring node in cluster B, The result is improved connectivity between these two clusters.

  Both MNDB and TNDB have better network connectivity, shorter paths (and hence reduced end-to-end delay) and both omnidirectional antennas and random directional beamforms. Achieve lower interference. These algorithms can be further improved by using additional information from neighboring nodes such as available energy, congestion level and channel quality. This reduces the cost of operating the network while increasing user satisfaction (eg, reducing battery consumption of mobile devices, increased network capacity, etc.). Furthermore, it is possible to consider neighboring nodes that are farther than 2 hops (3 hops, 4 hops,..., N hops).

  According to one embodiment, status information or information about the neighborhood is periodically transmitted at predetermined intervals by each node. The first transmission time can be selected at random within a certain timing window after the node starts operation, for example. Subsequent transmissions (beacons or piggybacked data packets) can occur at predetermined intervals, but according to one embodiment, the intervals vary somewhat randomly.

  By introducing randomness to the timing of beamform direction selection at the start and possibly subsequent selections, multiple beamform direction selections can be made simultaneously (this is the stability of the network Which can negatively affect sex). On the other hand, by providing regular intervals (which can be changed to some extent randomly) and selecting the beamform direction during that time, the network will respond to changes in the situation mainly due to node movement. It is guaranteed to adapt continuously and regularly.

  As a further embodiment, the order in which individual nodes transmit is either predetermined or fixed. In other words, the order in which individual nodes select the beamform direction remains the same. However, such a fixed order requires minimal adjustment between individual nodes to at least establish the order. This is a bit more complicated than when each node chooses the timing of its selection, incorporating random elements that ensure that the selection process is more or less distributed in time.

  Next, some examples to which embodiments of the present invention can be applied will be described.

  Consider a sensor network in which network elements (sensors) use beam antennas. Compared to sensors that use omni-directional antennas, beam antennas help increase transmission rate and transmission range, save energy, extend sensor life, and improve network connectivity. However, some sensors may be disconnected from other parts of the network due to topology heterogeneity (topology boundaries, empty areas, etc.). Choosing the beamform direction using embodiments of the present invention helps to find the direction in which all sensors connect better to the network (other parts).

  Another example to which embodiments of the present invention can be applied is a vehicle network.

  Consider a network of vehicle nodes connected wirelessly using a beam antenna. Vehicles can exchange emergency information, traffic information, etc. using either single-hop communication or multi-hop communication. Selecting a beamform direction using embodiments of the present invention helps the vehicle direct its beam in a direction that increases connectivity. It also helps to adapt the topology dynamics so that the vehicle does not direct its beam to “sky” areas (eg, lakes, highway roadsides). Beamform generally helps to expand radio range, and using the embodiments of the present invention to select the beamform direction further “correct” to shorten the end-to-end path and reduce packet delay. "Useful for choosing beamform direction."

  Another example to which embodiments of the present invention can be applied is an auto-configurable radio-access network (Auto-configurable Radio-Access Networks).

  In a radio access network, an access point using a beam antenna increases its transmission range (and its reception gain) in a given direction. Selecting beamform directions using embodiments of the present invention further covers more users, adapts to topology dynamics (eg, which conference room in the hotel is used) and the user's It helps to adapt the directivity of the antenna beam to increase satisfaction.

  Another example to which the embodiments of the present invention can be applied is an auto-configurable mesh network (Auto-configurable Mesh Networks).

  As an extension of the above radio access network example, elements in a mesh network can use the embodiments of the present invention to improve network connectivity, reduce interference and adapt to accidental network dynamics. Can do.

  Those skilled in the art will appreciate that the above embodiments can be implemented by hardware, software or a combination of software and hardware. The modules described in connection with embodiments of the present invention may be implemented in whole or in part by a microprocessor or computer appropriately programmed to perform the methods described in connection with embodiments of the present invention. Can do.

It is a figure for demonstrating schematically the beamform mechanism of a prior art. It is a schematic block diagram of the apparatus by one Embodiment of this invention. It is a schematic block diagram of the node by one Embodiment of this invention. FIG. 6 shows an algorithm executed by an apparatus according to an embodiment of the present invention. It is a figure which shows roughly an example of the beam form condition of this invention. It is a figure which shows roughly another example of the beam form condition of this invention.

Claims (14)

An apparatus for selecting a beamform direction of a node in a wireless network,
A control module that changes the beam angle in individual steps and controls the beamform direction of the antenna connected to the device;
A receiving module that overhears an ongoing transmission and extracts one or more neighboring parameters indicating transmission overheared at different angle steps;
The control module calculates a determination parameter for each angle step, compares the determination parameter of the different angle step, and selects an angle corresponding to the optimal determination parameter as the beamform direction of the antenna based on the comparison result der which is,
The neighborhood parameters sent by a node include the number of neighborhood nodes in an angle step,
The angle in the beamform direction of the antenna that maximizes the number of neighboring nodes is selected,
The number of neighboring nodes is the number of neighboring nodes that can be reached within n hops, where n is a number greater than or equal to one . The apparatus according to claim 1 , wherein the proximity parameter is included in data transmission or a dedicated beacon message in a layer lower than a layer in which a routing protocol operates. The neighborhood parameter transmitted by the node is :
And server Tterireberu,
Congestion level,
Channel quality,
Including one or more of relative or absolute positions and
When considering two or more neighboring parameters, a cumulative judgment parameter is calculated for each angle based on the plurality of neighboring parameters.
Apparatus according to any one of claims 1 or 2 . The control module is
Sweeping neighboring nodes by changing the beam direction by a predetermined angle;
Overhearing transmission of data packets by neighboring nodes and transmission of beacons by neighboring nodes when a beacon message is used;
Maintaining each angle direction for a predetermined time before moving to the next angle;
Configuring a determination parameter F (P) based on a set P of status parameters including all received related neighborhood parameters p_k (k = 1,..., M);
Using a new beam direction if F (P) increases with a certain beam direction and is greater than a threshold above a previous value;
Or regular intervals, or in which additionally executes a step of repeating the steps based on the manual trigger, device according to any one of claims 1-3. The control module may either or both of the step size of the angle increment during the sweep and the step time at an angle to obtain a statistically significant sample of status updates in the corresponding direction. it is intended to adapt the apparatus according to any one of claims 1-4. The neighborhood parameters are intended to be transmitted or sent by piggybacked the node for normal traffic or by using a dedicated beacon message for transmitting said neighborhood parameters, Claim 1-5 The apparatus as described in any one of. A module that changes a threshold applied to determine whether a change in the decision parameter is sufficient to change the beamform direction, when detecting that the network is very unstable apparatus according to any one of claims 1 to 6, comprising a module when detecting is intended to reduce the threshold that either increase the threshold, and / or network is very stable . Which receives said neighborhood parameters from neighbors at a distance of hops 1, based on the neighborhood parameters received from the neighboring node at the distance of the hop number 1, according to claim 1 to 7 for calculating the decision parameter The device according to any one of the above. Receiving the neighborhood parameter from a neighborhood node having a hop count of 2 or more;
Apparatus according to any one of claims 1 to 8 and a step of calculating said decision parameter based on the neighborhood parameters received from the neighboring node that includes a neighborhood node the number of hops is in two or more distance . Apparatus according to any one of claims 1 to 9 for determining the decision parameter based on the maximum number of detected neighboring node at a certain angle. 11. The module according to any one of claims 1 to 10 , comprising a module for randomly selecting the timing of the first beamform selection performed by a node and selecting the timing of subsequent beamform selection at regular intervals. Equipment. 12. The apparatus of claim 11 , wherein the regular interval varies according to a random parameter selected by the module. Apparatus according to any one of claims 1 to 12, comprising a timing selection module for determining the order in which nodes in the network performs the beamforming selection. A network including a plurality of nodes comprising the device according to any one of claims 1 to 13 ,
A sensor network,
A vehicle network,
A wireless mesh network,
A network that is either a wireless access network.

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