Decentralized Estimation over Orthogonal Multiple-access Fading Channels in Wireless Sensor Networks - Optimal and Suboptimal Estimators

Optimal and suboptimal decentralized estimators in wireless sensor networks (WSNs) over orthogonal multiple-access fading channels are studied in this paper. Considering multiple-bit quantization before digital transmission, we develop maximum likelihood estimators (MLEs) with both known and unknown channel state information (CSI). When training symbols are available, we derive a MLE that is a special case of the MLE with unknown CSI. It implicitly uses the training symbols to estimate the channel coefficients and exploits the estimated CSI in an optimal way. To reduce the computational complexity, we propose suboptimal estimators. These estimators exploit both signal and data level redundant information to improve the estimation performance. The proposed MLEs reduce to traditional fusion based or diversity based estimators when communications or observations are perfect. By introducing a general message function, the proposed estimators can be applied when various analog or digital transmission schemes are used. The simulations show that the estimators using digital communications with multiple-bit quantization outperform the estimator using analog-and-forwarding transmission in fading channels. When considering the total bandwidth and energy constraints, the MLE using multiple-bit quantization is superior to that using binary quantization at medium and high observation signal-to-noise ratio levels

Opportunistic Relaying in Wireless Networks

Relay networks having $n$ source-to-destination pairs and $m$ half-duplex relays, all operating in the same frequency band in the presence of block fading, are analyzed. This setup has attracted significant attention and several relaying protocols have been reported in the literature. However, most of the proposed solutions require either centrally coordinated scheduling or detailed channel state information (CSI) at the transmitter side. Here, an opportunistic relaying scheme is proposed, which alleviates these limitations. The scheme entails a two-hop communication protocol, in which sources communicate with destinations only through half-duplex relays. The key idea is to schedule at each hop only a subset of nodes that can benefit from \emph{multiuser diversity}. To select the source and destination nodes for each hop, it requires only CSI at receivers (relays for the first hop, and destination nodes for the second hop) and an integer-value CSI feedback to the transmitters. For the case when $n$ is large and $m$ is fixed, it is shown that the proposed scheme achieves a system throughput of $m/2$ bits/s/Hz. In contrast, the information-theoretic upper bound of $(m/2)\log \log n$ bits/s/Hz is achievable only with more demanding CSI assumptions and cooperation between the relays. Furthermore, it is shown that, under the condition that the product of block duration and system bandwidth scales faster than $\log n$, the achievable throughput of the proposed scheme scales as $\Theta ({\log n})$. Notably, this is proven to be the optimal throughput scaling even if centralized scheduling is allowed, thus proving the optimality of the proposed scheme in the scaling law sense.Comment: 17 pages, 8 figures, To appear in IEEE Transactions on Information Theor

Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity

We investigate asymptotic capacity limits of the Gaussian MIMO broadcast channel (BC) with spatially correlated fading to understand when and how much transmit correlation helps the capacity. By imposing a structure on channel covariances (equivalently, transmit correlations at the transmitter side) of users, also referred to as \emph{transmit correlation diversity}, the impact of transmit correlation on the power gain of MIMO BCs is characterized in several regimes of system parameters, with a particular interest in the large-scale array (or massive MIMO) regime. Taking the cost for downlink training into account, we provide asymptotic capacity bounds of multiuser MIMO downlink systems to see how transmit correlation diversity affects the system multiplexing gain. We make use of the notion of joint spatial division and multiplexing (JSDM) to derive the capacity bounds. It is advocated in this paper that transmit correlation diversity may be of use to significantly increase multiplexing gain as well as power gain in multiuser MIMO systems. In particular, the new type of diversity in wireless communications is shown to improve the system multiplexing gain up to by a factor of the number of degrees of such diversity. Finally, performance limits of conventional large-scale MIMO systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure

Achievable Rates, Optimal Signalling Schemes and Resource Allocation for Fading Wireless Channels

The proliferation of services involving the transmission of high rate data traffic over wireless channels makes it essential to overcome the detrimental effects of the wireless medium, such as fading and multiuser interference. This thesis is devoted to obtaining optimal resource allocation policies which exploit the transmitters' and receiver's knowledge about the fading to the network's advantage, to attain information theoretic capacity limits of fading wireless channels. The major focus of the thesis is on capacity results for fading code division multiple access (CDMA) channels, which have proved to be a robust way of combatting the multiuser interference in practical wireless networks. For these channels, we obtain the capacity region achievable with power control, as well as the power control policies that achieve the desired rate points on the capacity region. We provide practical one-user-at-a-time iterative algorithms to compute the optimal power distributions as functions of the fading. For the special case of sum capacity, some properties of the optimal policy, such as the number of simultaneously transmitting users, are obtained. We also investigate the effects of limited feedback on the capacity, and demonstrate that very coarse channel state information (CSI) is sufficient to benefit from power control as a means of increasing the capacity. The selection of the signature sequences also plays an important role in determining the capacity of CDMA systems. This thesis addresses the problem of jointly optimizing the signature sequences and power levels to maximize the sum capacity. The resulting policies are shown to be simple, consisting of orthogonal transmissions in time or signal space, and requiring only local CSI. We also provide an iterative way of updating the joint resource allocation policy, and extend our results to asynchronous, and multi-antenna CDMA systems. Rather than treating the received signal at the transmitters as interference, it is possible to treat it as free side information and use it for cooperation. The final part of the thesis provides power allocation policies for a fading Gaussian multiple access channel with user cooperation, which maximize the rates achievable by block Markov superposition coding, and also simplify the coding strategy

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

Cooperative Communications with Partial Channel State Information in Mobile Radio Systems

Future 4G mobile radio cellular networks are considered OFDM-MIMO systems. Cooperative communication based on coordinated base stations is a very promising concept to perform inter-cell interference management. This thesis deals with the concept of cooperative communication from its information-theoretic background to its practical system design. The main focus is a practical design of the joint detection scheme in the uplink and the joint transmission scheme in the downlink with partial channel-state information (CSI), i.e., significant CSI and imperfect CSI.Zukünftige zellulare 4G-Mobilfunksysteme können als OFDM-MIMO-Systeme betrachtet werden. In solchen zukünftigen Mobilfunksystemen ist kooperative Kommunikation, basierend auf koordinierten Basisstationen, ein sehr vielversprechendes Konzept zum Interzellinterferenzmanagement. Die vorliegende Arbeit behandelt das Konzept der kooperativen Kommunikation vom informationstheoretischen Hintergrund bis hin zum praktischen Systemdesign. Der Schwerpunkt der vorliegenden Arbeit liegt auf dem praktischen Design kooperativer Kommunikationssysteme mit partieller Kanalkenntnis