Spatial Modulation Aided Zero-Padded Single Carrier Transmission for Dispersive Channels

Spatial modulation (SM) is a transmission scheme that uses multiple transmit antennas but only one transmit RF chain. At each time instant, only one among the transmit antennas will be active and the others remain silent. The index of the active transmit antenna will also convey information bits in addition to the information bits conveyed through modulation symbols. Pseudo-random phase precoding (PRPP) is a technique that can achieve high diversity orders even in single antenna systems without the need for channel state information at the transmitter and transmit power control. In this paper, we exploit the advantages of both SM and PRPP simultaneously. We propose a pseudo-random phase precoded SM (PRPP-SM) scheme, where both the modulation bits and the antenna index bits are precoded by pseudo-random phases. The proposed PRPP-SM system gives significant performance gains over SM system without PRPP and PRPP system without SM. Since maximum likelihood (ML) detection becomes exponentially complex in large dimensions, we propose a low complexity local search based detection (LSD) algorithm suited for PRPP-SM systems with large precoder sizes. Our simulation results show that with 4 transmit antennas, 1 receive antenna, 5 × 20 pseudo-random phase precoder matrix and BPSK modulation, the performance of PRPP-SM using ML detection is better than SM without PRPP with ML detection by about 9 dB at 102 BER. This performance advantage gets even better for large precoding sizes. We also propose a precoder index modulation (PIM) scheme, which conveys additional information bits through the choice of a precoding matrix among a set of pre-determined PRPP matrices. Finally, combining the PIM and PRPP-SM schemes, we propose a PIM-SM scheme which conveys bits through both antenna index as well as precoder index.

In this paper, we design an implementation of a kind of reduced-complexity maximum likelihood (ML) detector for spatial modulation (SM) deployed in a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. Based on National Instruments Universal Software Radio Peripheral (NI USRP) platform, two USRP Reconfigurable Input / Output (USRP-RIO) devices are used as the transmitter and the receiver. Error performance comparisons between the reduced-complexity ML detector and conventional ML detector are made in an indoor environment, as well as the comparison between SM scheme and space-frequency block code (SFBC) scheme. 6 different pictures are exploited as transmitted data, and are reconstructed in the receiver side, so the performance of each scheme is taken on the reconstructed pictures. Both of the calculated bit error ratio (BER) and the reconstruction result of each transmitted pictures, validate the highly consistent error performance of HL_ML detector and conventional ML detector, as well as the error performance superiority of SM over SFBC.

Generalized space shift keying (GSSK) proposed for large scale MIMO systems promises significant advantages in terms of hardware costs. However, the maximum likelihood (ML) detection for GSSK is computationally intractable. Detection schemes using compressive sensing (CS) offer a favorable performance-complexity tradeoff. In this letter, we propose a novel GSSK detection framework, where CS algorithms are used to reduce the complexity of ML detection. The proposed framework significantly reduces the performance gap between existing CS-based detection schemes and ML detection while retaining the complexity advantage of CS algorithms. Simulation results demonstrate the superiority of proposed scheme over popular CS-based detection schemes.

A low complexity maximum likelihood (ML) detection method is proposed for the square quadrature amplitude modulation (QAM) constellation. In order to reduce the implementation complexity of ML detection, set-partition, subset-selection, and subset-shift are recursively applied to the square QAM constellation. The estimated square QAM symbol is finally given in a closed form as a function of the received signal and the estimated channel. Complexity analysis and numerical simulation confirm that the proposed detection method reduces the implementation complexity substantially and achieves exactly the same performance as the conventional ML detection irrespective of the channel estimation error.

Recently, a maximum likelihood (ML) detection rule for differential unitary space time modulation (DUSTM) under the existence of unknown carrier frequency offset (CFO) has been derived. However, the ML detection is based on the exhaustive search over all the unitary group codes. In this paper, we design an efficient detection algorithm for newly derived ML rule, by modifying the bound intersection detector (BID). Our proposed algorithm is seen as a generalization of the existing BID that is known to be an optimal detector for the conventional DUSTM. The simulation results show that the proposed algorithm can save a large portion of the computational complexity compared to the naive searching method.

In spatial modulation (SM) systems, when channel state information is available at the transmitter, adaptive power allocation can be exploited to enhance the SM performance. In this paper, optimal power allocation in SM systems is considered from an information-theoretical view. First, as there is no closed-form expression of the SM capacity, the instantaneous mutual information is formulated in an analytic form for SM systems with two transmit antennas. Then, two power-allocation algorithms are proposed to maximize the SM mutual information. One is a sub-optimal power-allocation algorithm that is established in closed form to maximize the upper bound of SM mutual information. The other is an iterative algorithm for optimal power allocation that is proposed to achieve the maximum mutual information of SM systems while dramatically reducing the operational complexity compared with global computer searching. To evaluate the performance of the proposed power-allocation algorithms, numerical and simulation results are reported in terms of outage capacity and ergodic capacity, which demonstrates that the proposed power-allocation algorithms significantly improve the SM performance, compared with conventional equal-power allocation.

The Spatial Modulation (SM) transmission scheme boosts the spectral efficiency and achieves the multiplexing gain by activating a single transmit antenna in each time slot. Radio wave propagation characteristics determined by the environment is a decisive factor for the SM system. In this paper, we investigate the performance of the SM scheme over real-world 4×4 Multi-Input Multi-Output (MIMO) channels measured in typical indoor scenarios. Firstly, a MIMO channel sounder is established. Based on the sounder, 15150 complex 4×4 MIMO channel matrices are measured inside a typical teaching building under both Line of Sight (LOS) and None Line of Sight (NLOS) scenarios. Secondly, by comparing the SM system over the measured channel and commonly-used channel models, we prove that both the Independently and Identically Distribute (i.i.d.) Rayleigh and the Spatial Correlation (SC) channel model are oversimplified, and that only practical experiences can yield definitive answers to the achievable real-world system performance. Thirdly, the Average Bit Error Probability (ABEP) performance of the SM system is studied based on the measured data under a variety of system configurations. The study of different receive antenna array settings (4×4, 4×2 and 4×1 MIMO setups) approves the significance of combining scheme at the receiver. SM systems employing different signal constellations (Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) and 16 Quadrature Amplitude Modulation (16QAM)) are also investigated and some interesting results are revealed. Lastly, performance assessment of SM against State-Of-The-Art (SOTA) MIMO schemes (Space-Time Block Code (STBC) and Vertical Bell Labs Layered Space-Time (V-BLAST) code) is conducted. Results show that for a 4×4 MIMO, the low-complexity SM scheme outperforms both STBC and V-BLAST.

In this paper, a common framework for maximum likelihood (ML) detection of spatial multiplexed (SM) and space time coded multiple-input multiple-output (MIMO) signals is proposed. It facilitates a common field programmable gate array (FPGA) based hardware design for the detection of both SM and space time block coded (STBC) MIMO signals with reduced computational complexity. We reduce the number of multipliers required for the ML detection by utilizing a set of precomputed combinations of the constellation symbols from lookup tables (LUT) without any degradation in the packet error rate (PER) performance. The reduction in the computational complexity is achieved by using the additional memory that is available in the FPGA. To evaluate the performance of the proposed method, we perform simulations for the WLAN system based on IEEE 802.11 standard using SM-MIMO and STBC-MIMO.

In this manuscript, a novel transmit pre-coding matrix generation method and a linear decoding scheme are proposed for the generalised pre-coding aided spatial modulation (GPSM) system. The GPSM scheme proposed recently is a new multiple input multiple output (MIMO) transmission technique, which conveys information by activating a subset of receive antennas with the aid of transmit pre-coding. This scheme seems to be suitable in V2X since the base station only transmits data to certain users/vehicles. The proposed pre-coding matrix is based on the lattice reduction (LR) principle and provides significant performance improvement over the original pre-coding design in GPSM. Furthermore, as the GPSM in large-scale antenna systems, which is a trend in future communication systems, might be too complex to be implemented with the maximum likelihood (ML) detection, a linear decoding method is proposed to reduce the implementation complexity. Our studies show that the performance degradation caused by the linear detector can be compensated by the proposed LR based pre-coding. As a result, the LR based GPSM with linear detection is capable of achieving the comparable performance as that of the original GPSM scheme employing ML detection, while with significantly decreased detection complexity.

One of the main limitations in Spatial Modulation (SM) systems is the lack of transmit diversity, which directly impacts its error rate performance. The lack of the transmit diversity refers to activating only a single transmit antenna in SM systems. In this paper, we propose a novel scheme that aims at improving the performance of SM systems by achieving half-full transmit diversity. The proposed scheme, called Half-Full Transmit-Diversity SM (HFTD-SM), divides the transmit antennas into two-antenna groups. From each group, only a single antenna is activated, and all active transmit antennas emits one modulated symbol. The proposed HFTD-SM scheme is shown to outperform the conventional SM performance in terms of spectral efficiency, error rate, and design flexibility, while maintaining the main property of SM representing by the need of only a single RF chain. Simulation results corroborate the superior performance of the proposed scheme as compared to other SM variants in the literature.

Feasibility of applying genetic algorithms in space-time block coded multiuser detection systems

Orthogonal space-time block codes (OSTBCs) have attracted much attention owing to their simple code construction, maximal diversity gain, and low maximum-likelihood (ML) detection complexity when channel state information (CSI) is available at the receiver. This paper addresses the problem of ML OSTBC detection with unknown CSI. Focusing on the binary and quaternary PSK constellations, we show that blind ML OSTBC detection can be simplified to a Boolean quadratic program (BQP). From an optimization viewpoint the BQP is still a computationally hard problem, and we propose two alternatives for dealing with this inherent complexity. First, we consider the semidefinite relaxation (SDR) approach, which leads to a suboptimal, but accurate, blind ML detection algorithm with an affordable worst-case computational cost. We also consider the sphere decoding approach, which leads to an exact blind ML detection algorithm that remains computationally expensive in the worst case, but generally incurs a reasonable average computational cost. For the two algorithms, we study implementation methods that can significantly reduce the computational complexity. Simulation results indicate that the two blind ML detection algorithms are competitive, in that the bit error performance of the two algorithms is almost the same and is noticeably better than that of some other existing blind detectors. Moreover, numerical studies show that the SDR algorithm provides better complexity performance than the sphere decoder in the worst-case sense, and vice versa in the average sense.

In this paper we propose a low complexity receiver structure of MIMO Interleaved SC-FDMA (Multiple Input Multiple Output Interleaved Single Carrier-Frequency Division Multiple Access) on frequency selective channels. The receiver firstly obtains the tentative decision results through FDE (Frequency Domain Equalization) and using the tentative results the ISI (Inter-Symbol Interference) is cancelled by the ISI canceller. Then the MLD (Maximum Likelihood Detection) is utilized to separate the spatially multiplexed signal streams to obtain the decision results. By regarding the decision results as the improved tentative decision results, the ISI cancellation and MLD are iteratively done. However, as the complexity of MLD is quite high, we replace the MLD by the SD (Sphere Decoding). As the complexity of SD is still high for high level modulations, we adopt the combination of IAI (Inter-Antenna Interference) canceller and the MRC (Maximum Ratio Combining) instead of the SD. We examined the BER characteristics and the complexity reduction of proposed receiver structure using the ISI + IAI canceller and MRC with iterative detection and verified the effectiveness of the proposed receiver structure.

In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed for a cooperative diffusion-based molecular communication (MC) system. In this system, a fusion center (FC) chooses the transmitter's symbol that is more likely, given the likelihood of the observations from multiple receivers (RXs). We propose three different ML detection variants according to different constraints on the information available to the FC, which enables us to demonstrate trade-offs in their performance versus the information available. The system error probability for one variant is derived in closed form. Numerical and simulation results show that the ML detection variants provide lower bounds on the error performance of the simpler cooperative variants and demonstrate that majority rule detection has performance comparable to ML detection when the reporting is noisy.

Future wireless communication systems being char- acterized by tight frequency reuse, adaptive modulation and coding schemes and diversified data services will be interfer- ence limited by the interfering signals of diverse rates and strengths. Frequency reuse factor of 1 being proposed for the next generation mobile systems will lead to 1 or 2 dominant interferers. We propose in this paper a low complexity maximum likelihood (ML) demodulator for interference suppression. The proposed demodulator is also applicable to general multi-stream (spatially multiplexed) MIMO systems where it reduces one complex dimension of the system i.e. the complexity of ML detection reduces from O (|χ| n ) to O � |χ| n�1 � where n is number of transmit antennas/spatial streams. This is a fundamental result as space and technology constraints shall be restricting future MIMO systems to low dimensionality. Therefore reduction of one complex dimension in detection shall enable implementation of ML detectors at the receivers. We look at the performance of linear MMSE demodulator and the proposed demodulator in the presence of interferers of diverse strengths and rates and simulation results demonstrate much improved performance of the proposed demodulator for interference suppression.