Hyun Jong Yang

Achievable Sum-Rate Maximizing AF Relay Beamforming Scheme in Two-Way Relay Channels

This paper deals with design of a amplify-and- forward (AF) relay beamforming matrix in a two-way relay protocol when a relay node has multiple antennas. Two-way relaying is a promising protocol since it provides enhanced spectral efficiency compared to one-way relaying protocols. In this paper we derive the achievable sum-rate upper bound of AF beamforming scheme and propose the achievable sum-rate maximizing relay beamforming scheme when the destination and the relay node have perfect knowledge of the channel state information (CSI) for forward and backward channels. The solution of the sum-rate maximizing scheme is obtained by using the proposed algorithm, general power iterative algorithm, which solves a global optimization problem efficiently. Comparing with one-way relaying protocol, the improved sum-rate performance of the proposed scheme is verified by numerical simulation.

Opportunistic Interference Alignment for MIMO Interfering Multiple-Access Channels

We consider the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N users having L antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by SNR(K-1)S, where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to SNR(K-1)S-L+1 through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

Asymptotic Capacity of the Separated MIMO Two-Way Relay Channel

A multiple-input multiple-output two-way relay channel consisting of two communication nodes and a full-duplex relay node in which no direct link exists between the two communication nodes is considered. We propose an achievable scheme that employs horizontally encoded lattice codes combined with generalized singular value decomposition-based precoding for the first phase. The second phase of the proposed scheme follows the fundamentals of the previous scheme, which uses vertically encoded structural bining, with the only difference that the added codeword of the two codewords from the communication nodes, instead of those two individual codewords, is decoded and retransmitted in the proposed scheme. We show that the proposed scheme achieves the cut-set bound asymptotically as the signal-to-noise ratios of the channels tend to infinity.

Modified High-Order PAMs for Binary Coded Physical-Layer Network Coding

The non-binary code (NBC) or the lattice code (LC) has been the only possible channel code with the pulse amplitude modulation (PAM) signaling of modulation size greater than two for the physical layer network coding (PNC) over a decode-and-forward (DF) relaying channel. A major drawback with the NBC or LC however is its high computational complexity. In this letter, we present new modified high-order PAMs that enable us to use the computationally efficient binary channel coding under the PNC over a DF relaying channel.

Distributed Sum-Rate Optimization for Full-Duplex MIMO System Under Limited Dynamic Range

Distributed sum-rate-maximizing covariance matrices design for full-duplex multi-input multi-output communication is considered, where the information of the loopback interference channels cannot be exchanged reliably due to their large dynamic ranges. We propose a structured covariance matrices design which finds the optimal balance between the two solutions in the extremes of the weak and strong self-interference through a single-parameter optimization. We further propose a low-complexity null projection matrix design algorithm, in which the solution in the strong self-interference regime is designed in the sense to maximize the received channel gain. Exploiting the well-posed structure, the proposed scheme nearly achieves the sum-rate of the previous scheme based on the gradient projection with significantly less amount of inter-node iterations, yielding an increased effective sum-rate and reduced overall complexity for the practial channel block lengths.

Zero-Forcing Based Two-phase Relaying

In cellular mobile communication systems, the link performance can be remarkably improved by deploying relays between the base station and the mobile station. In this paper we propose an efficient duplexing scheme so that both spatial and temporal gain by adding relays can be increased. Using the proposed relaying scheme, the conventional system of four-phase relaying can be simplified to a two-phase relaying system and the additional resource consumption due to relays can be minimized. We show the capacity gain for cell edge users with numerical results.

Achievable Sum-Rate of MU-MIMO Cellular Two-Way Relay Channels: Lattice Code-Aided Linear Precoding

We derive a new sum-rate lower bound of the multiuser multi-input multi-output (MU-MIMO) cellular two-way relay channel (cTWRC) which is composed of a base station (BS) and a relay station (RS), both with multiple antennas, and non-cooperative mobile stations (MSs), each with a single antenna. In the first phase, we show that network coding based on decode-and-forward relaying can be generalized to arbitrary input cardinality through proposed lattice code-aided linear precoding, despite the fact that precoding is permitted only at the BS due to non-cooperation among the MSs. In addition, a new sum-rate lower bound for the second phase is derived by showing that the two spatial decoding orders at the BS and MSs for one-sided zero-forcing dirty-paper-coding must be identical. From the fundamental gain of network coding, our sum-rate lower bound achieves the full multiplexing gain regardless of the number of antennas at the BS or RS, and strictly exceeds the previous lower bound which is based on traditional multiuser decoding in the first phase. Furthermore, it is shown that our lower bound asymptotically achieves the sum-rate upper bound in the presence of signal-to-noise ratio (SNR) asymmetry in high SNR regime, and sufficient conditions for this SNR asymmetry are drawn.

Opportunistic downlink interference alignment

We introduce an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that compared to the existing downlink IA schemes, the minimum number of users required to achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e., the fundamental user scaling law can be improved, by using the ODIA. In addition, we introduce a limited feedback strategy in our ODIA framework, and then analyze the minimum number of feedback bits required to obtain the same performance as that of the ODIA assuming perfect feedback.

Zero-forcing-based two-phase relaying with multiple mobile stations

It is well known that relay stations improve the link performance between the base and mobile stations and thereby improve the total system throughput. Nonetheless, the additional resource consumption to deploy the relay station reduces the system throughput significantly. The zero-forcing (ZF)-based two-phase relaying scheme that requires only two phases to communicate a frame was suggested for the system where a single mobile station is considered. The performance bottle-necks of the conventional ZF-based two-phase relaying are channel asymmetry and an ill-conditioned channel that reduces the effective channel gain. We propose a novel two-phase relaying scheme to support multiple users simultaneously for a given channel resource. The proposed relaying scheme includes the multiuser scheduling at the relay station and the additional precoding at the base station to make the effective channels from the base and mobile stations equal to each other. We evaluate the proposed relaying scheme by numerically comparing its sum rate to those of the conventional relaying schemes.

A Closed-Form Power Allocation and Signal Alignment for a Diagonalized MIMO Two-Way Relay Channel With Linear Receivers

A novel channel diagonalization scheme for an amplify-and-forward, multiple-input multiple-output (MIMO), two-way relay channel (TWRC) is proposed using generalized singular value decomposition (GSVD). Diagonalization of the MIMO TWRC is a sub-optimal approach that achieves two main purposes: reducing the computational complexity for optimizing the linear precoders at each node; and reducing the detection complexity at the source nodes by separating the multiple data streams. For the given diagonalized structure, we first align the entries of the diagonalized channels using a permutation to maximize a lower bound of average achievable sum rate (ASR), and a joint source-relay power allocation is then performed to maximize the ASR of the aligned TWRC; the overall problem is divided into two convex subproblems, the solutions to which are provided in closed-form. Our analysis for the proposed scheme underlines the benefits of acquiring channel state information. Simulation results demonstrate that the proposed GSVD-based relaying scheme, with the signal alignment and closed-form power allocation, significantly improves the ASR while retaining the diagonalized channel structure. In addition, the proposed scheme achieves the same level of ASR with much less computational complexity as compared to the iterative schemes.