Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems

In this paper, we propose a MIMO receiver algorithm that exploits {\em channel hardening} that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the ${\bf H}^H{\bf H}$ matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix ${\bf H}$ increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes ${\bf H}^T{\bf H}{\bf x}$, where ${\bf x}$ is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the ${\bf H}^T{\bf H}$ matrix. We also propose a simple estimation scheme which directly obtains an estimate of ${\bf H}^T{\bf H}$ (instead of an estimate of ${\bf H}$), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the {\em channel hardening-exploiting message passing (CHEMP)} receiver. The proposed CHEMP receiver achieves very good performance in large-scale MIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of ${\bf H}$. We also present a convergence analysis of the proposed MPD algorithm. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes

On the Capacity and Performance of Generalized Spatial Modulation

Generalized spatial modulation (GSM) uses $N$ antenna elements but fewer radio frequency (RF) chains ($R$) at the transmitter. Spatial modulation and spatial multiplexing are special cases of GSM with $R=1$ and $R=N$, respectively. In GSM, apart from conveying information bits through $R$ modulation symbols, information bits are also conveyed through the indices of the $R$ active transmit antennas. In this paper, we derive lower and upper bounds on the the capacity of a ($N,M,R$)-GSM MIMO system, where $M$ is the number of receive antennas. Further, we propose a computationally efficient GSM encoding (i.e., bits-to-signal mapping) method and a message passing based low-complexity detection algorithm suited for large-scale GSM-MIMO systems.Comment: Expanded version of the IEEE Communications Letters pape

Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems

Generalized spatial modulation (GSM) uses $n_t$ transmit antenna elements but fewer transmit radio frequency (RF) chains, $n_{rf}$. Spatial modulation (SM) and spatial multiplexing are special cases of GSM with $n_{rf}=1$ and $n_{rf}=n_t$, respectively. In GSM, in addition to conveying information bits through $n_{rf}$ conventional modulation symbols (for example, QAM), the indices of the $n_{rf}$ active transmit antennas also convey information bits. In this paper, we investigate {\em GSM for large-scale multiuser MIMO communications on the uplink}. Our contributions in this paper include: ($i$) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and ($ii$) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR). The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of $10^{-3}$. Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.Comment: IEEE Trans. on Wireless Communications, accepte

Coded Index Modulation for Non-DC-Biased OFDM in Multiple LED Visible Light Communication

Use of multiple light emitting diodes (LED) is an attractive way to increase spectral efficiency in visible light communications (VLC). A non-DC-biased OFDM (NDC OFDM) scheme that uses two LEDs has been proposed in the literature recently. NDC OFDM has been shown to perform better than other OFDM schemes for VLC like DC-biased OFDM (DCO OFDM) and asymmetrically clipped OFDM (ACO OFDM) in multiple LEDs settings. In this paper, we propose an efficient multiple LED OFDM scheme for VLC which uses {\em coded index modulation}. The proposed scheme uses two transmitter blocks, each having a pair of LEDs. Within each block, NDC OFDM signaling is done. The selection of which block is activated in a signaling interval is decided by information bits (i.e., index bits). In order to improve the reliability of the index bits at the receiver (which is critical because of high channel correlation in multiple LEDs settings), we propose to use coding on the index bits alone. We call the proposed scheme as CI-NDC OFDM (coded index NDC OFDM) scheme. Simulation results show that, for the same spectral efficiency, CI-NDC OFDM that uses LDPC coding on the index bits performs better than NDC OFDM

Gender and Job Performance: Evidence from Wall Street

We study the relation between gender and job performance among brokerage firm equity analysts. Women's representation in analyst positions drops from 16% in 1995 to 13% in 2005. We find women cover roughly 9 stocks on average compared to 10 for men. Women's earnings estimates tend to be less accurate. After controlling for forecast characteristics, the difference in accuracy is roughly equivalent to four years of experience. Despite reduced coverage and lower forecast accuracy, we find women are significantly more likely to be designated as All-Stars, which suggests they outperform at other aspects of the job such as client service.