Regenerative and Adaptive schemes Based on Network Coding for Wireless Relay Network

Recent technological advances in wireless communications offer new opportunities and challenges for relay network.To enhance system performance, Demodulate-Network Coding (Dm-NC) scheme has been examined at relay node; it works directly to De-map the received signals and after that forward the mixture to the destination. Simulation analysis has been proven that the performance of Dm-NC has superiority over analog-NC. In addition, the Quantize-Decode-NC scheme (QDF-NC) has been introduced. The presented simulation results clearly provide that the QDF-NC perform better than analog-NC. The toggle between analogNC and QDF-NC is simulated in order to investigate delay and power consumption reduction at relay node.Comment: 11 pages, 8 figures, International Journal of Computer Networks & Communications (IJCNC), Vol.4, No.3, May 201

A novel quantize-and-forward cooperative system : channel parameter estimation techniques

The Quantize and Forward cooperative communication protocol improves the reliability of data transmission by allowing a relay to forward to the destination a quantized version of the signal received from the source. In prior studies of the Quantize and Forward protocol, all channel parameters are assumed to be perfectly known at the destination, while in reality these need to be estimated. This paper proposes a novel Quantize and Forward protocol in which the relay compensates for the rotation on the source-relay channel using a crude channel estimate, before quantizing the phase of the received M-PSK data symbols. Therefore, as far as the source-relay channel is concerned, only an SNR estimate is needed at the destination. Further, the destination applies the EM algorithm to improve the estimates of the source-destination and relay-destination channel coefficients. The resulting performance is shown to be close to that of a system with known channel parameters

Joint Power Control and Fronthaul Rate Allocation for Throughput Maximization in OFDMA-based Cloud Radio Access Network

The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal quantization/compression techniques in the fronthaul to maximize the network throughput. However, most of the previous results are based on information-theoretical quantization methods, which are hard to implement due to the extremely high complexity. In this paper, we consider using practical uniform scalar quantization in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN system, where the mobile users are assigned with orthogonal sub-carriers for multiple access. In particular, we consider joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system end-to-end throughput. Efficient algorithms are proposed to solve the joint optimization problem when either information-theoretical or practical fronthaul quantization method is applied. Interestingly, we find that the fronthaul capacity constraints have significant impact to the optimal wireless power control policy. As a result, the joint optimization shows significant performance gain compared with either optimizing wireless power control or fronthaul quantization alone. Besides, we also show that the proposed simple uniform quantization scheme performs very close to the throughput performance upper bound, and in fact overlaps with the upper bound when the fronthaul capacity is sufficiently large. Overall, our results would help reveal practically achievable throughput performance of C-RAN, and lead to more efficient deployment of C-RAN in the next-generation wireless communication systems.Comment: submitted for possible publicatio

PRACTICAL QUANTIZE-AND-FORWARD SCHEMES FOR THE FREQUENCY RELAY CHANNEL

International audienceWe consider static and quasi-static relay channels in which the source-destination and relay-destination signals are assumed to be orthogonal and thus have to be recombined at the destination. We propose cheap relaying schemes that are optimized from the knowledge of the signal-to-noise ratios (SNRs) of the source-relay and relay-destination channels at the relay. For this purpose the scheme under investigation is assumed to be scalar and have to minimize the mean square error between the source signal and its reconstructed version at the destination. We propose a quantize-and-forward (QF) scheme, which is a generalization of techniques based on joint source-channel coding. To further improve the receiver performance when the source-relay SNR is relatively poor we propose a Maximum Likelihood detector (MLD) designed for the QF protocol

The Cramer-Rao Bound for channel estimation in block fading amplify-and-forward relaying networks

In this paper, we express the Cramer-Rao Bound (CRB) for channel coefficient and noise variance estimation at the destination of an Amplify-and- Forward (AF) based cooperative system, in terms of the a posteriori expectation of the codewords. An algorithm based on factor graphs can be applied in order to calculate this expectation. As the computation of the CRB is rather intensive, the modified CRB (MCRB), which is a looser bound, is derived in closed form. It can be shown that the MCRB coincides with the CRB in the high signal-to-noise ratio (SNR) limit and to that end the CRB/MCRB ratio is simulated in case of uncoded and convolutional encoded transmission

Wireless Network Information Flow: A Deterministic Approach

In a wireless network with a single source and a single destination and an arbitrary number of relay nodes, what is the maximum rate of information flow achievable? We make progress on this long standing problem through a two-step approach. First we propose a deterministic channel model which captures the key wireless properties of signal strength, broadcast and superposition. We obtain an exact characterization of the capacity of a network with nodes connected by such deterministic channels. This result is a natural generalization of the celebrated max-flow min-cut theorem for wired networks. Second, we use the insights obtained from the deterministic analysis to design a new quantize-map-and-forward scheme for Gaussian networks. In this scheme, each relay quantizes the received signal at the noise level and maps it to a random Gaussian codeword for forwarding, and the final destination decodes the source's message based on the received signal. We show that, in contrast to existing schemes, this scheme can achieve the cut-set upper bound to within a gap which is independent of the channel parameters. In the case of the relay channel with a single relay as well as the two-relay Gaussian diamond network, the gap is 1 bit/s/Hz. Moreover, the scheme is universal in the sense that the relays need no knowledge of the values of the channel parameters to (approximately) achieve the rate supportable by the network. We also present extensions of the results to multicast networks, half-duplex networks and ergodic networks.Comment: To appear in IEEE transactions on Information Theory, Vol 57, No 4, April 201