109 research outputs found

    Generalized Adaptive Network Coding Aided Successive Relaying Based Noncoherent Cooperation

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    A generalized adaptive network coding (GANC) scheme is conceived for a multi-user, multi-relay scenario, where the multiple users transmit independent information streams to a common destination with the aid of multiple relays. The proposed GANC scheme is developed from adaptive network coded cooperation (ANCC), which aims for a high flexibility in order to: 1) allow arbitrary channel coding schemes to serve as the cross-layer network coding regime; 2) provide any arbitrary trade-off between the throughput and reliability by adjusting the ratio of the source nodes and the cooperating relay nodes. Furthermore, we incorporate the proposed GANC scheme in a novel successive relaying aided network (SRAN) in order to recover the typical 50% half-duplex relaying-induced throughput loss. However, it is unrealistic to expect that in addition to carrying out all the relaying functions, the relays could additionally estimate the source-to-relay channels. Hence noncoherent detection is employed in order to obviate the power-hungry channel estimation. Finally, we intrinsically amalgamate our GANC scheme with the joint network-channel coding (JNCC) concept into a powerful three-stage concatenated architecture relying on iterative detection, which is specifically designed for the destination node (DN). The proposed scheme is also capable of adapting to rapidly time-varying network topologies, while relying on energy-efficient detection

    Successive-relaying-aided decode-and-forward coherent versus noncoherent cooperative multicarrier space–time shift keying

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    Abstract—Successive-relaying-aided (SR) cooperative multi-carrier (MC) space–time shift keying (STSK) is proposed for frequency-selective channels. We invoke SR to mitigate the typical 50% throughput loss of conventional half-duplex relaying schemes and MC code-division multiple access (MC-CDMA) to circumvent the dispersive effects of wireless channels and to reduce the SR-induced interference. The distributed relay terminals form two virtual antenna arrays (VAAs), and the source node (SN) successively transmits frequency-domain (FD) spread signals to one of the VAAs, in addition to directly transmitting to the destination node (DN). The constituent relay nodes (RNs) of each VAA activate cyclic-redundancy-checking-based (CRC) selective decode-and-forward (DF) relaying. The DN can jointly detect the signals received via the SN-to-DN and VAA-to-DN links using a low-complexity single-stream-based joint maximum-likelihood (ML) detector. We also propose a differentially encoded cooperative MC-CDMA STSK scheme to facilitate communications over hostile dispersive channels without requiring channel estimation (CE). Dispensing with CE is important since the relays cannot be expected to altruistically estimate the SN-to-RN links for simply supporting the source. Furthermore, we propose soft-decision-aided serially concatenated recursive systematic convolutional (RSC) and unity-rate-coded (URC) cooperative MC STSK and investigate its performance in both coherent and noncoherent scenarios

    Forwarding strategies and optimal power allocation for coherent and noncoherent relay networks

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    In fading wireless channels, relays are used with the aim of achieving diversity and thus overall performance gain. In cooperative relay networks, various forwarding techniques like amplify and forward (AF) and decode and forward (DF) are used at the relay for better throughput and improved BER performance than traditional multihop systems. In a power constrained environment, the performance can be further improved by using an optimal power allocation strategy. The relative position of the relay with respect to the source and destination also has an immense effect on the efficacy of the relay.;We position the relay at various positions in a planar grid, with the position of source and destination being fixed, and we investigate the effect that the positioning of the relay has on a relaying system. We use our three terminal model to optimize the power allocation under total transmit power constraint, to maximize the instantaneous signal-to-noise ratio (SNR) at destination, and thus achieve improved throughput and BER performance, while using AF and DF protocols. We evaluate the performance of our system for both coherent and noncoherent modulation in a Rayleigh block fading channel. Quadrature phase shift keying (QPSK) is used in the coherent case and 4-Frequency shift keying (4-FSK) is used in the noncoherent case.;Previous works involving power allocation schemes have mainly concentrated on optimizing information theoretic quantities like capacity and outage probability. We derive expressions for instantaneous SNR using our model and optimize the power allocation based on that, with the final aim of achieving improved uncoded BER. Analytical expressions of the instantaneous SNR at the destination are derived for both AF and DF. These expressions are numerically optimized to obtain an optimum power allocation strategy for each position of the relay in both the AF and DF schemes using coherent or noncoherent detection.;We compare the performance of the AF and DF protocols based on their positional BER and throughput at different received SNR and notice that our power optimized schemes outperform existing power control schemes at certain areas. Finally we also identify the shape and area of the regions where relaying would provide performance gains for both the protocols at different received SNRs

    Design guidelines for spatial modulation

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    A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants

    Distributed Self-Concatenated Coding for Cooperative Communication

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    In this paper, we propose a power-efficient distributed binary self-concatenated coding scheme using iterative decoding (DSECCC-ID) for cooperative communications. The DSECCC-ID scheme is designed with the aid of binary extrinsic information transfer (EXIT) charts. The source node transmits self-concatenated convolutional coded (SECCC) symbols to both the relay and destination nodes during the first transmission period. The relay performs SECCC-ID decoding, where it mayor may not encounter decoding errors. It then reencodes the information bits using a recursive systematic convolutional (RSC) code during the second transmission period. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel concatenated encoder. At the destination node, three-component DSECCC-ID decoding is performed. The EXIT chart gives us an insight into operation of the distributed coding scheme, which enables us to significantly reduce the transmit power by about 3.3 dB in signal-to-noise ratio (SNR) terms, as compared with a noncooperative SECCC-ID scheme at a bit error rate (BER) of 10-5. Finally, the proposed system is capable of performing within about 1.5 dB from the two-hop relay-aided network’s capacity at a BER of 10-5 , even if there may be decoding errors at the relay
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