This paper considers lattice decoding for multi-input multi-output (MIMO) detection under PAM constellations. A key aspect of lattice decoding is that it relaxes the symbol bound constraints in the optimal maximum-likelihood (ML) detector for faster implementations. It is known that such a symbol bound relaxation may lead to a damaging effect on the system… (More)
This paper considers robust constant envelope (CE) precoding with antenna-subset selection (AS) in a large-scale MISO downlink scenario where only imperfect channel state information at the transmitter (CSIT) is available. CE precoding is a recently proposed transmission scheme that enables the use of cheap but highly power-efficient power amplifiers, while… (More)
This paper describes a new approximate maximum-likelihood (ML) MIMO detection approach by studying a Lagrangian dual relaxation (LDR) of ML. Unlike many existing relaxed ML methods, the proposed LDR employs a discrete domain for the problem formulation. We find that the proposed LDR exhibits an intriguing relationship to the lattice decoders (LDs) and the… (More)
In this paper, we study the amplify-and-forward (AF) schemes in two-hop one-way relay networks. In particular, we consider the multigroup multicast transmission between long-distance users. Given that perfect channel state information is perceived, our goal is to design the AF process so that the max-min-fair (MMF) signal-to-interference-plus-noise ratio… (More)
This paper concentrates on a robust transmit optimization problem for the multiuser multi-input single-output (MISO) downlink scenario and under inaccurate channel state information (CSI). This robust problem deals with a general-rank transmit covariance design and follows a safe rate-constrained formulation under spherically bounded CSI uncertainties.… (More)
— This is a companion technical report of the main manuscript " Semidefinite Relaxation and Approximation Analysis of a Beamformed Alamouti Scheme for Relay Beamforming Networks ". The report serves to give detailed derivations of Lemma 1-2 in the main manuscript, which are too long to be included in the latter. In addition, more simulation results are… (More)
This technical report provides the proof of Proposition 1 in  which claims that the following optimization problem is NP-hard. min a∈R N a T 1 (1a) s.t.