Decoding scheme for relay networks with parity forwarding cooperation protocol

Abstract

The maximum a posterior (MAP) decoding scheme is presented here for cooperative communication networks that adopt the parity forwarding as a cooperation protocol. The MAP decoder is optimal in the sense that it minimises the error probability. The authors consider a wireless network that is composed of two sources: two relays and a single destination. A closed-form expression is derived for upper bound on the bit error probability. The complexity of derivation comes from the fact that although the source generates data with equal probability, the data received at the destination does not have the same a priori probability. That is because of the error that occurs in the source-to-relay link. Therefore, the MAP decoding rule cannot be simplified to the maximum likelihood decoding rule. The results show that the analytical upper bound is very tight and almost coincides with the exact error probability obtained from simulations at higher values of the signal-to-noise ratio. Accordingly, the closed-form expression of the upper bound can be used to fully study and understand the diversity performance of the system.

New beamforming and space‐time coding for two‐path successive decode and forward relaying

“…Using the two following integrals and relations (115) and (116) and some algebraic manipulations [14][15][16][17][18][19][20][21][22][23][24][25], Y k = ∫ ν k ∞ Q (2γ b /5)X k P(X k | X k > ν k ) dX k can be obtained as given in relation (51) [23][24][25]. We use Craig's formula for this derivation [25] Calculation of the probability of erroneous detection at MIMO relay k (Υ k ′ ) after transition of MIMO inter-relay channel…”

“…Also, it does not employ STC and beamforming for performance improvement. A decoding scheme for relay networks with parity forwarding cooperation protocol has been proposed in [22] that employs maximum a posteriori for decoding symbols and imposes high computational complexity. Moreover, it does not achieve full diversity order and in the case of using ML, there exists error floor in high SNR regime.…”

Bit error rate performance analysis of AC-MAP in multiple input single output wireless relay network

“…The maximum a posteriori (MAP) decoder was proposed and its BER performance was analyzed in [15,16] for single input single output (SISO) wireless relay network. Unlike other decoders, the receiver does not use any combining techniques.…”

Analysis of Channel Coding Performance for Image Transmission Over Cooperative Relay Networks

“…They benefit from the nature of transmission provided by the wireless medium, whereby the transmitted signals can be received and processed by any device in the coverage area of the transmitter [13][14][15]. The main idea of network coding [16] is that information that comes from multiple sources is mixed (encoded), to boost the reliability of decoding at the destination. The literature has suggested many communication protocols [17], such as decoding and forwarding (DF), amplification and forwarding (AF), and compression and forward (CF).…”

“…In this work, we consider the DF protocol as a communication protocol. The decoding scheme proposed in [16] presents the maximum a posterior decoder (MAP) for cooperative communication networks as the relay devices combine data received from sources to create the parity bits that are forwarded to the destination. The Genetic algorithm (GA), as an advanced optimization technique, is derived from the notion of natural evolution based on the Darwinian theory of "survival of the fittest" by Holland [18].…”