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Minimal CDMA Recoding Strategies in Power-Controlled Ad-Hoc Wireless Networks

This paper discusses minimal recoding strategies for power-controlled ad-hoc wireless networks, focusing on handling collisions and efficient code assignment. It introduces new recoding strategies and simulation results. The goal is to minimize recoding while ensuring optimal performance in dynamic network scenarios. The proposed algorithms aim to eliminate primary and secondary collisions and minimize the maximum code index assigned to any network node. Distributed and local communication are key features of these strategies.

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Minimal CDMA Recoding Strategies in Power-Controlled Ad-Hoc Wireless Networks

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  1. Minimal CDMA Recoding Strategies in Power-Controlled Ad-Hoc Wireless Networks Honglei Miao honglei.miao@ee.oulu.fiCentre for Wireless CommunicationsUniversity of Oulu, Finland

  2. Outline • Introduction • Problem statement and previous work • New recoding strategies • Simulation Results • Conclusions

  3. Introduction • Transmitter Oriented Code Assignment (TOCA) in CDMA based Ad-Hoc wireless network • Each node is assigned one code to be used to transmit it’s message. • Two kinds of collisions can be happened to damage the transmission. • Primary collision where an incoming transmission is damaged by a simultaneous outgoing transmission from the receiving mobile. • Secondary collision where two incoming transmissions garble each other. • Correct and efficient TOCA algorithms should be: • Eliminate all the collisions including primary and secondary collisions. • Minimize the maximum code index assigned to any network node. • Several centralized and distributed heuristics have been proposed for static multihop networks. • Why recoding in Ad-Hoc network? • In a dynamic ad-hoc network, nodes are free to • move about. • connect or disconnect from the network. • Increase or decrease transmission ranges. • These events may introduce new collisions, Recoding is needed to eliminate these new collisions.

  4. Introduction (2) • Existed code assignment algorithms are inappropriate for recoding • Centralized code assignment algorithms determine a new code assignment for every node on each event. (costly) • Distributed heuristics assume a static network. (inappropriate) • Minimum recoding algorithms are proposed in this paper. • Distributed, only need communication local to the event. • Minimal recoding, minimize the number of the nodes to be recoded on any network. • Least increase in the maximum code index assigned to the network.

  5. Problem statement and previous work • A power controlled ad-hoc network is modelled as a dynamic directed graph G=(V,E). • V = {v1,v2,….,vn} is set of nodes in the network. ri is the transmission range of node vi. ci is the code assigned to node vi. • E = {(vi, vj): i !=j, and dij<=ri} is the set of the directed edges. • TOCA is to assign a code to each node in the network so that the following two constraints are satisfied. • CA1-(Primary) collision avoidance 1: For every edge • CA2-(Secondary) collision avoidance 2: For every pair of edges

  6. Problem statement and previous work (2) • Assumption of the events or reconfiguration in the dynamic ad-hoc network • Events occur one after another and not simultaneously. • Nodes move and change their ranges in discrete steps. • Minimal connectivity: A node v can change its configuration iff it has both from-neighbour and to-neighbour. • The goals of an efficient recoding strategy • Minimize the maximum code index used by any node in the network. (hardware consideration) • Minimize the number of nodes that change their codes. • Minimize the overhead of the recoding • Keep the recoding strategy distributed and local.

  7. Problem statement and previous work (3) • Previous strategy: CP strategy • The new node and its 1-hop neighbours exchange the information about their old codes and constraints. • Ordering by identities • The new nodes and it’s 1-hop neighbours need to be recoded continuously check if they are the highest (or lowest)-identity node in its vicinity that has not been assigned a code. • Respect for the constraints • If it is the highest (or lowest)-identity node. The lowest available code (not taken by any 1-hop and 2-hop neighbours) is selected.

  8. New recoding strategies • Handling Node Join

  9. New recoding strategies (2) • From CA1 and CA2, all nodes in 1n, 2n, {n} each need to have codes different from each other. Nodes in 3n need not change their codes since n will be assigned a new code anyway and this will need to be different from any of the codes in 3n. • If a K-sized subset of nodes in 1n U 2n have the same old code, only K-1 nodes need to be changed. • More generally, if they are K nodes in 1n U 2n , and m different codes in 1n U 2n, then only K-m nodes need to be changed to different codes.

  10. New recoding strategies (3) • Algorithm for recoding on a node join

  11. New recoding strategies (4) • Example of recoding on a node join • 1n = {7}, 2n = {1 2 3 6}, 3n = {}, 4n = {4 5}

  12. New recoding strategies (5) • Handling Node Power Increase

  13. New recoding strategies (6) • No new constraints are induced among 1n U 2n U 3n U 4n. • All constraints due to CA1 and CA2 added by the new edges involve node n. • Minimum recoding only change the code of n if the old code of n can not satisfy the new constraints. • However, the proposed algorithm may not be the optimal among all minimal recoding strategies. For example, n only have one new constraint with another node m. If n has lots of old constraints and m very few, recoding only m might be more optimal in terms of maximum code index assigned to the network while achieving the minimal recoding bound.

  14. New recoding strategies (7) • Handling Node Leaves and Power Decreases • No recoding since no new conflicts are introduced. • Handling Node Movement • Node movement is treated as a pair of consecutive events where the moving node n leaves and joins the network. • Recoding strategy on a node move is similar to that on a node join.

  15. Simulation results • The different algorithms are simulated for a long sequence of events. • The proposed algorithms are compared to • BBB algorithm: centralized colouring heuristic, recolor all the nodes at every event. • CP strategy • The performance metrics to be concerned • Maximum code index assigned in the network (the lower the better). • The number of nodes recoded (recoded with a new code different from its old one).

  16. Simulation results (2)

  17. Simulation results (3)

  18. Simulation results (4)

  19. Conclusions • A set of recoding strategies Minim for TOCA CDMA recoding in a dynamic ad-hoc network are proposed. • Given an event, the strategy change the codes of the minimum number of mobiles needed to eliminate all collisions in the network. • Simulation results reveal that the Minim approaches trade off a relatively small loss in terms of maximum code index assigned in the network to obtain a significant gain in terms of the total number of instances where a node has to change its code. • The proposed strategies can be very practical in scenarios such as hard real-time systems and high data rate applications running on an ad-hoc network.

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