On the Non-Orthogonal Layered Broadcast Codes in Cooperative Wireless Networks

A multi-fold increase in spectral efficiency and throughput are envisioned in the fifth generation of cellular networks to meet the requirements of International Telecommunication Union (ITU) IMT-2020 on massive connectivity and tremendous data traffic. This is achieved by evolution in three aspects of current networks. The first aspect is shrinking the cell sizes and deploying dense picocells and femtocells to boost the spectral reuse. The second is to allocate more spectrum resources including millimeter-wave bands. The third is deploying highly efficient communications and multiple access techniques. Non-orthogonal multiple access (NOMA) is a promising communication technique that complements the current commercial spectrum access approach to boost the spectral efficiency, where different data streams/users’ data share the same time, frequency and code resource blocks (sub-bands) via superimposition with each other. The receivers decode their own messages by deploying the successive interference cancellation (SIC) decoding rule. It is known that the NOMA coding is superior to conventional orthogonal multiple access (OMA) coding, where the resources are split among the users in either time or frequency domain. The NOMA based coding has been incorporated into other coding techniques including multi-input multi-output (MIMO), orthogonal frequency division multiplexing (OFDM), cognitive radio and cooperative techniques. In cooperative NOMA codes, either dedicated relay stations or stronger users with better channel conditions, act as relay to leverage the spatial diversity and to boost the performance of the other users. The advantage of spatial diversity gain in relay-based NOMA codes, is deployed to extend the coverage area of the network, to mitigate the fading effect of multipath channel and to increase the system throughput, hence improving the system efficiency. In this dissertation we consider the multimedia content delivery and machine type communications over 5G networks, where scalable content and low complexity encoders is of interest. We propose cross-layer design for transmission of successive refinement (SR) source code interplayed with non-orthogonal layered broadcast code for deployment in several cooperative network architectures. Firstly, we consider a multi-relay coding scheme where a source node is assisted by a half-duplex multi-relay non-orthogonal amplify-forward (NAF) network to communicate with a destination node. Assuming the channel state information (CSI) is not available at the source node, the achievable layered diversity multiplexing tradeoff (DMT) curve is derived. Then, by taking distortion exponent (DE) as the figure of merit, several achievable lower bounds are proved, and the optimal expected distortion performance under high signal to noise ratio (SNR) approximation is explicitly obtained. It is shown that the proposed coding can achieve the multi-input single-output (MISO) upper bound under certain regions of bandwidth ratios, by which the optimal performance in these regions can be explicitly characterized. Further the non-orthogonal layered coding scheme is extended to a multi-hop MIMO decode-forward (DF) relay network where a set of DE lower bounds is derived. Secondly, we propose a layered cooperative multi-user scheme based on non-orthogonal amplify-forward (NAF) relaying and non-orthogonal multiple access (NOMA) codes, aiming to achieve multi-user uplink transmissions with low complexity and low signaling overhead, particularly applicable to the machine type communications (MTC) and internet of things (IoT) systems. By assuming no CSI available at the transmitting nodes, the proposed layered codes make the transmission rate of each user adaptive to the channel realization. We derive the close-form analytical results on outage probability and the DMT curve of the proposed layered NAF codes in the asymptotic regime of high SNR, and optimize the end-to-end performance in terms of the exponential decay rate of expected distortion. Thirdly, we consider a single relay network and study the non-orthogonal layered scheme in the general SNR regime. A layered relaying scheme based on compress-forward (CF) is introduced, where optimization of end to end performance in terms of expected distortion is conducted to jointly determine network parameters. We further derive the explicit analytical optimal solution with two layers in the absence of channel knowledge. Finally, we consider the problem of multicast of multi-resolution layered messages over downlink of a cellular system with the assumption of CSI is not available at the base station (BS). Without loss generality, spatially random users are divided into two groups, where the near group users with better channel conditions decode for both layers, while the users in the second group decode for base layer only. Once the BS launches a multicast message, the first group users who successfully decoded the message, deploy a distributed cooperating scheme to assist the transmission to the other users. The cooperative scheme is naive but we will prove it can effectively enhance the network capacity. Closed form outage probability is explicitly derived for the two groups of users. Further it is shown that diversity order equal to the number of users in the near group is achievable, hence the coding gain of the proposed distributed scheme fully compensate the lack of CSI at the BS in terms of diversity order

Rate-Splitting Multiple Access for 6G Networks: Ten Promising Scenarios and Applications

In the upcoming 6G era, multiple access (MA) will play an essential role in achieving high throughput performances required in a wide range of wireless applications. Since MA and interference management are closely related issues, the conventional MA techniques are limited in that they cannot provide near-optimal performance in universal interference regimes. Recently, rate-splitting multiple access (RSMA) has been gaining much attention. RSMA splits an individual message into two parts: a common part, decodable by every user, and a private part, decodable only by the intended user. Each user first decodes the common message and then decodes its private message by applying successive interference cancellation (SIC). By doing so, RSMA not only embraces the existing MA techniques as special cases but also provides significant performance gains by efficiently mitigating inter-user interference in a broad range of interference regimes. In this article, we first present the theoretical foundation of RSMA. Subsequently, we put forth four key benefits of RSMA: spectral efficiency, robustness, scalability, and flexibility. Upon this, we describe how RSMA can enable ten promising scenarios and applications along with future research directions to pave the way for 6G.Comment: 17 pages, 6 figures, submitted to IEEE Network Magazin

Resource allocation for layered broadcast over relay-assisted channels

The topic of this thesis is on the application of “multilayer transmission” using the broadcast approach on a “relay-assisted” channel. Unlike single layer transmission, where all transmitted information bits have the same protection level by the channel coding scheme, multilayer transmission schemes combine successive refinement layered source coding with ordered protection levels of the source layers. Consequently, the receiver will be able to decode “some” information when the channel is faded and “all” information when the channel is good. The multilayer transmission schemes have gained a lot of interest in the information theory and the communication theory literature, where most researchers are interested in the “broadcast approach” since it is the optimal transmission strategy. In this thesis, we consider a fading relay channel where the source uses layered source coding with successive refinement. The source layers are transmitted using superposition coding at the source with optimal resource allocation. The destination applies successive interference cancellation after optimally combining the direct and relayed signals. The resource allocation for the layers is subject to optimization in order to maximize the expected user satisfaction that is usually defined by a differentiable concave increasing utility function of the total decoded rate at the destination. As special cases, we consider two utility functions; namely, the expected total decoded rate at the receiver and the expected rate distortion of a Gaussian source. We also assume that only the channel statistics are known at the receiver. The relay is half-duplex and applies different relaying strategies, and we have investigated the Amplify-and-Forward, and Decode-and-Forward strategies in particular. First, we consider the case of Decode-and-Forward relays where we consider two layers only with predetermined rates for simplicity, and we solve the problem of optimal power allocation among the two layers at the source and the relay using random search methods. After that, we solve the optimal power allocation problem for any number of layers with fixed rates over an Amplify-and-Forward relays. An approximation for the end-to-end channel quality is presented in terms of the statistics of the three links of the channel model. Furthermore, we obtain that for some conditions, it is optimal to send only one layer. Finally, we solve the joint optimal power and rate allocation problem for any number of layers over an Amplify-and-Forward relays. We also consider the theoretical case of infinite number of layers representing an upper bound for the performance. Moreover, we show that with a small number of layers, we can approach the performance upper bound. We provide many numerical examples for the three cases above to show the prospected gains of using the relays on the expected utility for different channel conditions

Optimization for beamforming problems in wireless networks

Beamforming in wireless communications have gathered great interests in recent years due to its ability to enhanced the performance of networks significantly by exploiting intensively the spatial diversity. In this work, the objectives of beamforming design consist of several optimization targets ranging from minimizing the beamforming power subject to quality-of-service (QoS) constraints to maximizing the minimum QoS regarding fixed budgets of transmitting power. The design problems of beamforming are intrinsically challenging because their natural formulations are nonconvex optimization problems. Moreover several problems are proved to be non-deterministic polynomial-time hard (NP-hard) such as beamforming in multicast transmission. These problems are very difficult to solve at optimality in practical sense. Therefore, there is a strong motivation to convert the original design problems into a series of convex problems with desirable computational complexity by applying efficient optimization techniques. This dissertation contributes mainly in exploiting the convex optimization algorithms to solve nonconvex beamforming problems in several network settings. First, the transmit beamforming for downlink communication of multicast transmission with spectrum sharing is investigated. Secondly, the beamforming design is applied on amplify-forward (AF) wireless relaying systems using single-antenna relays. The key contribution is to derive the beamforming schemes applied on transmit antennas so that the beamforming power is minimized while all users' signal-to-interference-and-noise ratios (SINRs) are guaranteed. The formulation results in nonconvex optimization problems due to SINR constraints hence require to be converted into semidefinite programming (SDP) forms. The SDP problems are again nonconvex regarding the rank-one constraints on semidefinite variables. Conventionally, the rank-one constraints are relaxed hence the problems cannot be solved thoroughly. In this work, nonsmooth optimization techniques are employed to tackle with the nonconvex rank-one constraints and are successfully to deliver efficient solutions that can outperform the conventional methods. Finally the precoding design problems in mutiple-input multiple-output (MIMO) relaying scenarios are considered. The difference-of-two-convex-function (D.C.) programming technique is employed to solve the problems at optimality with significantly lower complexity compared with conventional method

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access(SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user downlink network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa