Link-State Based Decode-Forward Schemes for Two-way Relaying

In this paper, we analyze a composite decode-and-forward scheme for the two-way relay channel with a direct link. During transmission, our scheme combines both block Markov coding and an independent coding scheme similar to network coding at the relay. The main contribution of this work is to examine how link state impacts the allocation of power between these two distinct techniques, which in turn governs the necessity of each technique in achieving the largest transmission rate region. We analytically determine the link-state regimes and associated relaying techniques. Our results illustrate an interesting trend: when the user-to-relay link is marginally stronger than the direct link, it is optimal to use only independent coding. In this case, the relay need not use full power. However, for larger user-to-relay link gains, the relay must supplement independent coding with block Markov coding to achieve the largest rate region. These link-state regimes are important for the application of two-way relaying in 5G networks, such as in D2D mode or relay-aided transmission.Comment: To be presented at Globecom 2014, Emerging Technologies for 5G Wireless Cellular Networks (Wi5G

Multiple-Symbol Differential Sphere Detection Aided Successive Relaying in the Cooperative DS-CDMA Uplink

The conventional amplify-and-forward cooperative system is capable of achieving a superior performance with the aid of Multiple-Symbol Differential Sphere Detection (MSDSD), when compared to conventional differential detection (CDD) for transmission over time-selective channels. However, the conventional broadcast/cooperative twin-phase based relaying protocol encounters a 50% throughput loss imposed by half-duplex relaying. For combating this problem, in this paper, we create a MSDSD aided successive relaying based cooperative DS-CDMA system. We demonstrate that given the target BER of 10?4 , a diversity gain of up to 10 dB is achieved over the benchmark schemes employed without a throughput loss

Cooperative Lattice Coding and Decoding

A novel lattice coding framework is proposed for outage-limited cooperative channels. This framework provides practical implementations for the optimal cooperation protocols proposed by Azarian et al. In particular, for the relay channel we implement a variant of the dynamic decode and forward protocol, which uses orthogonal constellations to reduce the channel seen by the destination to a single-input single-output time-selective one, while inheriting the same diversity-multiplexing tradeoff. This simplification allows for building the receiver using traditional belief propagation or tree search architectures. Our framework also generalizes the coding scheme of Yang and Belfiore in the context of amplify and forward cooperation. For the cooperative multiple access channel, a tree coding approach, matched to the optimal linear cooperation protocol of Azarain et al, is developed. For this scenario, the MMSE-DFE Fano decoder is shown to enjoy an excellent tradeoff between performance and complexity. Finally, the utility of the proposed schemes is established via a comprehensive simulation study.Comment: 25 pages, 8 figure

Selective Coding Strategy for Unicast Composite Networks

Consider a composite unicast relay network where the channel statistic is randomly drawn from a set of conditional distributions indexed by a random variable, which is assumed to be unknown at the source, fully known at the destination and only partly known at the relays. Commonly, the coding strategy at each relay is fixed regardless of its channel measurement. A novel coding for unicast composite networks with multiple relays is introduced. This enables the relays to select dynamically --based on its channel measurement-- the best coding scheme between compress-and-forward (CF) and decode-and-forward (DF). As a part of the main result, a generalization of Noisy Network Coding is shown for the case of unicast general networks where the relays are divided between those using DF and CF coding. Furthermore, the relays using DF scheme can exploit the help of those based on CF scheme via offset coding. It is demonstrated via numerical results that this novel coding, referred to as Selective Coding Strategy (SCS), outperforms conventional coding schemes.Comment: To appear in International Symposium on Information Theory (ISIT) 201

Generalized Adaptive Network Coding Aided Successive Relaying Based Noncoherent Cooperation

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

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe