A Linear Network Coding Approach for Uplink Distributed MIMO Systems: Protocol and Outage Behavior

© 1983-2012 IEEE. A distributed multiple-input-multiple-output (MIMO) system consists of M users served by L distributed base stations (BSs) , where the BSs are connected to a central unit (CU) via L independent backhaul (BH) links. In this paper, we consider the design of an uplink distributed MIMO system where 1) the channel state information is not available at the transmitters and 2) the BH links are rate constrained. We propose a new linear network coding (LNC)-based protocol: the M users transmit simultaneously. Each BS generates N linear functions of the M users' messages, based on a preassigned LNC coefficient matrix. The CU collects N ·L linear functions from the L BSs and recovers all M users' messages by solving these linear functions. The decoding becomes successful if the linear functions has full rank M and fails if the linear functions are rank deficient. We derive the preassigned LNC coefficient matrix that minimizes the probability of rank deficiency. We then analyze the outage probability (OP) of the proposed scheme over a Rayleigh fading channel. We analytically show that as long as the BH rate is greater than the individual data rate of one user, the OP of the proposed scheme decays like 1/SNRL at high SNR. This is in contrast to the existing scheme whose OP decays like 1/SNRL. As the BH rate constraint approaches M times the data rate of one user, the performance of the proposed scheme is 10/L log10 (L!) dB away from that of the full MIMO scenario at high SNR. We also develop a structured way to efficiently construct the preassigned LNC coefficient matrix that yields the optimized OP performance. Numerical results show that the proposed scheme has significantly improved performance over existing schemes

A Signal-Space Aligned Network Coding Approach to Distributed MIMO

© 2016 IEEE. This paper studies an uplink distributed MIMO (DMIMO) system that consists of $K$ users and K distributed base stations (BSs), where the BSs are connected to a central unit (CU) via independent rate-constrained backhaul (BH) links. We propose a new signal-space aligned network coding scheme. First, a network coding generator matrix is selected subject to certain structural properties. Next, distributed linear precoding is employed by the users to create aligned signal-spaces at the BSs, according to the pattern determined by the network coding generator matrix. For each aligned signal-space at a BS, physical-layer network coding is utilized to compute the corresponding network-coded (NC) messages, where the actual number of NC messages forwarded to the CU is determined by the BH rate-constraint. We derive an achievable rate of the proposed scheme based on the existence of the NC generator matrix and signal-space alignment precoding matrices. For DMIMO with two and three BSs, the achievable rates and degrees of freedom (DoF) are evaluated and shown to outperform existing schemes. For example, for DMIMO with two BSs where each user and BS have N and N antennas, respectively, the proposed scheme achieves a DoF of 2 min N,N-1, if the BH capacity scales like 2 min (N,N-1) log SNR. This leads to greater DoF compared to that utilizes the strategy for interference channel, whose DoF is min (N,N right). Numerical results demonstrate the performance advantage of the proposed scheme

Distributed MIMO broadcasting: Reverse compute-and-forward and signal-space alignment

© 2002-2012 IEEE. We study a downlink distributed MIMO system where a central unit (CU) broadcasts messages to K′ users through K distributed BSS. The CU is connected to the BSS via K independent rate-constrained fronthaul (FH) links. The distributed BSS collectively serve the users through the air. We propose a new network coding based distributed MIMO broadcasting scheme, using reverse compute-and-forward and signal-space alignment. At the CU, a network coding generator matrix is employed for pre network coding of the users' messages. The network coded messages are forwarded to the BSS, where the FH rate-constraint determines the actual number of network-coded messages forwarded to the BSS. At the BSS, linear precoding matrices are designed to create a number of bins, each containing a bunch of spatial streams with aligned signal-spaces. At each user, post physical-layer network coding is employed to compute linear combinations over the NC messages with respect to the bins, which reverses the prenetwork coding and recovers the desired messages. We derive an achievable rate of the proposed scheme based on the existence of NC generator matrix, signal-space alignment precoding matrices, and nested lattice codes. Improved rate and degrees of freedom over existing interference alignment and compress-and-forward schemes are shown. Numerical results demonstrate the performance improvement, e.g., by as much as 70% increase in throughput over benchmark schemes

Lossy Compression for Compute-and-Forward in Limited Backhaul Uplink Multicell Processing

We study the transmission over a cloud radio access network in which multiple base stations (BS) are connected to a central processor (CP) via finite-capacity backhaul links. We propose two lattice-based coding schemes. In the first scheme, the base stations decode linear combinations of the transmitted messages, in the spirit of compute-and-forward (CoF), but differs from it essentially in that the decoded equations are remapped to linear combinations of the channel input symbols, sent compressed in a lossy manner to the central processor, and are not required to be linearly independent. Also, by opposition to the standard CoF, an appropriate multi-user decoder is utilized to recover the sent messages. The second coding scheme generalizes the first one by also allowing, at each relay node, a joint compression of the decoded equation and the received signal. Both schemes apply in general, but are more suited for situations in which there are more users than base stations. We show that both schemes can outperform standard CoF and successive Wyner-Ziv schemes in certain regimes, and illustrate the gains through some numerical examples.Comment: Submitted to IEEE Transactions on Communication

Cloud-aided wireless systems: communications and radar applications

This dissertation focuses on cloud-assisted radio technologies for communication, including mobile cloud computing and Cloud Radio Access Network (C-RAN), and for radar systems. This dissertation first concentrates on cloud-aided communications. Mobile cloud computing, which allows mobile users to run computationally heavy applications on battery limited devices, such as cell phones, is considered initially. Mobile cloud computing enables the offloading of computation-intensive applications from a mobile device to a cloud processor via a wireless interface. The interplay between offloading decisions at the application layer and physical-layer parameters, which determine the energy and latency associated with the mobile-cloud communication, motivates the inter-layer optimization of fine-grained task offloading across both layers. This problem is modeled by using application call graphs, and the joint optimization of application-layer and physical-layer parameters is carried out via a message passing algorithm by minimizing the total energy expenditure of the mobile user. The concept of cloud radio is also being considered for the development of two cellular architectures known as Distributed RAN (D-RAN) and C-RAN, whereby the baseband processing of base stations is carried out in a remote Baseband Processing Unit (BBU). These architectures can reduce the capital and operating expenses of dense deployments at the cost of increasing the communication latency. The effect of this latency, which is due to the fronthaul transmission between the Remote Radio Head (RRH) and the BBU, is then studied for implementation of Hybrid Automatic Repeat Request (HARQ) protocols. Specifically, two novel solutions are proposed, which are based on the control-data separation architecture. The trade-offs involving resources such as the number of transmitting and receiving antennas, transmission power and the blocklength of the transmitted codeword, and the performance of the proposed solutions is investigated in analysis and numerical results. The detection of a target in radar systems requires processing of the signal that is received by the sensors. Similar to cloud radio access networks in communications, this processing of the signals can be carried out in a remote Fusion Center (FC) that is connected to all sensors via limited-capacity fronthaul links. The last part of this dissertation is dedicated to exploring the application of cloud radio to radar systems. In particular, the problem of maximizing the detection performance at the FC jointly over the code vector used by the transmitting antenna and over the statistics of the noise introduced by quantization at the sensors for fronthaul transmission is investigated by adopting the information-theoretic criterion of the Bhattacharyya distance and information-theoretic bounds on the quantization rate

Compute-and-Forward: Harnessing Interference through Structured Codes

Interference is usually viewed as an obstacle to communication in wireless networks. This paper proposes a new strategy, compute-and-forward, that exploits interference to obtain significantly higher rates between users in a network. The key idea is that relays should decode linear functions of transmitted messages according to their observed channel coefficients rather than ignoring the interference as noise. After decoding these linear equations, the relays simply send them towards the destinations, which given enough equations, can recover their desired messages. The underlying codes are based on nested lattices whose algebraic structure ensures that integer combinations of codewords can be decoded reliably. Encoders map messages from a finite field to a lattice and decoders recover equations of lattice points which are then mapped back to equations over the finite field. This scheme is applicable even if the transmitters lack channel state information.Comment: IEEE Trans. Info Theory, to appear. 23 pages, 13 figure