2 research outputs found
Survivability and performance optimization in communication networks using network coding
The benefits of network coding are investigated in two types of communication networks: optical backbone networks and wireless networks. In backbone networks, network coding is used to improve survivability of the network against failures. In particular, network coding-based protection schemes are presented for unicast and multicast traffic models. In the unicast case, network coding was previously shown to offer near-instantaneous failure recovery at the bandwidth cost of shared backup path protection. Here, cost-effective polynomial-time heuristic algorithms are proposed for online provisioning and protection of unicast traffic. In the multicast case, network coding is used to extend the traditional live backup (1+1) unicast protection to multicast protection; hence called multicast 1+1 protection. It provides instantaneous recovery for single failures in any bi-connected network with the minimum bandwidth cost. Optimal formulation and efficient heuristic algorithms are proposed and experimentally evaluated. In wireless networks, performance benefits of network coding in multicast transmission are studied. Joint scheduling and performance optimization formulations are presented for rate, energy, and delay under routing and network coding assumptions. The scheduling component of the problem is simplified by timesharing over randomly-selected sets of non-interfering wireless links. Selecting only a linear number of such sets is shown to be rate and energy effective. While routing performs very close to network coding in terms of rate, the solution convergence time is around 1000-fold compared to network coding. It is shown that energy benefit of network coding increases as the multicast rate demand is increased. Investigation of energy-rate and delay-rate relationships shows both parameters increase non-linearly as the multicast rate is increased
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Network Coding for Multihop Wireless Networks: Joint Random Linear Network Coding and Forward Error Correction with Interleaving for Multihop Wireless Networks
Optimising the throughput performance for wireless networks is one of the
challenging tasks in the objectives of communication engineering, since wireless
channels are prone to errors due to path losses, random noise, and fading
phenomena. The transmission errors will be worse in a multihop scenario due to its
accumulative effects. Network Coding (NC) is an elegant technique to improve the
throughput performance of a communication network. There is the fact that the bit
error rates over one modulation symbol of 16- and higher order- Quadrature
Amplitude Modulation (QAM) scheme follow a certain pattern. The Scattered
Random Network Coding (SRNC) system was proposed in the literature to exploit
the error pattern of 16-QAM by using bit-scattering to improve the throughput of
multihop network to which is being applied the Random Linear Network Coding
(RLNC). This thesis aims to improve further the SRNC system by using Forward
Error Correction (FEC) code; the proposed system is called Joint RLNC and FEC
with interleaving.
The first proposed system (System-I) uses Convolutional Code (CC) FEC. The
performances analysis of System-I with various CC rates of 1/2, 1/3, 1/4, 1/6, and
1/8 was carried out using the developed simulation tools in MATLAB and compared
to two benchmark systems: SRNC system (System-II) and RLNC system (System-
III). The second proposed system (System-IV) uses Reed-Solomon (RS) FEC
code. Performance evaluation of System IV was carried out and compared to three
systems; System-I with 1/2 CC rate, System-II, and System-III. All simulations were
carried out over three possible channel environments: 1) AWGN channel, 2) a
Rayleigh fading channel, and 3) a Rician fading channel, where both fading
channels are in series with the AWGN channel. The simulation results show that
the proposed system improves the SRNC system. How much improvement gain
can be achieved depends on the FEC type used and the channel environment.Indonesian Government and the University of Bradfor