Low-complexity precoding for spatial modulation

© 2017 IEEE. In this paper, we investigate linear precoding for spatial modulation (SM) over multiple-input-multiple-output (MIMO) fading channels. With channel state information available at the transmitter, our focus is to maximize the minimum Euclidean distance among all candidates of SM symbols. We prove that the precoder design is a large-scale non-convex quadratically constrained quadratic program (QCQP) problem. However, the conventional methods, such as semi-definite relaxation and iterative concave-convex process, cannot tackle this challenging problem effectively or efficiently. To address this issue, we leverage augmented Lagrangian and dual ascent techniques, and transform the original large-scale non-convex QCQP problem into a sequence of subproblems. These subproblems can be solved in an iterative manner efficiently. Numerical results show that the proposed method can significantly improve the system error performance relative to the SM without precoding, and features extremely fast convergence rate with very low computational complexity

Bandwidth efficient spatial modulation by signalling in the power domain

We explore a bandwidth efficient transmission scheme that amalgamates multiple-input-multiple-output spatial multiplexing (SMX) with receive antenna based spatial modulation (RSM). The RSM here is applied to the combined spatial and power-level domain, not by activating and de-activating the receive antennas, but rather by choosing between two power levels {Ρι,Ρ2} for the received symbols in these antennas, such that all receive antennas are active and SMX can still be accommodated. This allows for the coexistence of RSM with SMX and the results show an increased bandwidth efficiency for the proposed scheme compared to both SMX and RSM. We further carry out a mathematical analysis to optimize the ratio between Pi and P2 for attaining the minimum error rates. Our analytical and simulation results demonstrate significant bandwidth efficiency gains for the proposed scheme compared to conventional SMX and RSM

Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink

Conventional spatial modulation (SM) is typically considered for transmission in the downlink of smallscale MIMO systems, where a single one of a set of say 2p antenna elements (AEs) is activated for implicitly conveying p bits. By contrast, inspired by the compelling benefits of large-scale MIMO (LS-MIMO) systems, here we propose a LS-SM-MIMO scheme for the uplink (UL), where each user having multiple AEs but only a single radio frequency (RF) chain invokes SM for increasing the UL-throughput. At the same time, by relying on hundreds of AEs but a small number of RF chains, the base station (BS) can simultaneously serve multiple users whilst reducing the power consumption. Due to the large number of AEs of the UL-users and the comparably small number of RF chains at the BS, the UL multi-user signal detection becomes a challenging large-scale under-determined problem. To solve this problem, we propose a joint SM transmission scheme and a carefully designed structured compressive sensing (SCS)-based multi-user detector (MUD) to be used at the users and BS, respectively. Additionally, the cyclic-prefix single-carrier (CPSC) is used to combat the multipath channels, and a simple receive AE selection is used for the improved performance over correlated Rayleigh-fading MIMO channels. We demonstrate that the aggregate SM signal consisting of multiple UL-users’ SM signals of a CPSC block appears the distributed sparsity. Moreover, due to the joint SM transmission scheme, aggregate SM signals in the same transmission group exhibit the group sparsity. By exploiting these intrinsically sparse features, the proposed SCS-based MUD can reliably detect the resultant SM signals with low complexity. Simulation results demonstrate that the proposed SCS-based MUD achieves a better signal detection performance than its counterparts even with higher UL-throughtput

Power-efficient space shift keying transmission via semidefinite programming

Space shift keying (SSK) transmission is a low-complexity complement to spatial modulation (SM) that solely relies on a spatial-constellation diagram for conveying information. The achievable performance of SSK is determined by the channel conditions, which in turn define the minimum Euclidean distance (MED) of the symbols in the received SSK constellation. In this contribution we concentrate on improving the power efficiency of SSK transmission via symbol pre-scaling. Specifically, we pose a pair of related optimization problems for a) enhancing the MED at reception while satisfying a given power constraint at the transmitter, and b) reducing the transmission power required for achieving a given MED. The resultant optimization problems are NP-hard, hence they are subsequently reformulated and solved via semidefinite programming. The results presented demonstrate that the proposed pre-scaling strategies are capable of enhancing the attainable performance of conventional SSK, while simultaneously extending its applicability and reducing the complexity of the existing pre-scaling schemes

Transmit antenna selection for multiple-input multiple-output spatial modulation systems

The benefits of transmit antenna selection (TAS) invoked for spatial modulation (SM) aided multiple-input multiple-output (MIMO) systems are investigated. Specifically, we commence with a brief review of the existing TAS algorithms and focus on the recently proposed Euclidean distance-based TAS (ED-TAS) schemes due to their high diversity gain. Then, a pair of novel ED-TAS algorithms, termed as the improved QR decomposition (QRD)-based TAS (QRD-TAS) and the error-vector magnitude-based TAS (EVM-TAS) are proposed, which exhibit an attractive system performance at low complexity. Moreover, the proposed ED-TAS algorithms are amalgamated with the low-complexity yet efficient power allocation (PA) technique, termed as TAS-PA, for the sake of further improving the system's performance. Our simulation results show that the proposed TAS-PA algorithms achieve signal-to-noise ratio (SNR) gains of up to 9 dB over the conventional TAS algorithms and up to 6 dB over the TAS-PA algorithm designed for spatial multiplexing systems

Energy-Efficient Spatial Modulation in Massive MIMO Systems by Means of Compressive Sensing

In this paper we propose a spatial modulation (SM) technique with improved energy efficiency (EE) for the multiple access channel (MAC) with a large number of antennas. The proposed scheme builds upon compressive sensing (CS) and accounts for the sparsity and structure of the signals transmitted via SM in multi-user scenarios to further improve the performance and reduce the complexity of linear detectors. In particular, the proposed technique incorporates additional prior knowledge to conventional CS-based approaches by exploiting the existence of a maximum number of active antennas per user when SM transmission is used in the MAC. The results presented in this paper show that the proposed algorithm offers both a) reduced complexity and b) improved performance compared to conventional CS and linear detection strategies and also allow us to determine the conditions under which the use of SM systems in the MAC is beneficial from an EE point of view