Full-Duplex Media-Based Modulation

This paper investigates the simultaneous wireless information and power transfer (SWIPT)-enabled cooperative non-orthogonal multiple access (NOMA) with full-duplex (FD) relaying. Two optimization problems are formulated to minimize the required transmit power with both full channel state information (CSI) and partial CSI (i.e., channel distribution information (CDI)). As both problems are non-convex without explicit solution methods, the semidefinite relaxation (SDR) is applied to relax them firstly. Then, for the full CSI case, a bilevel programming (BLP)-based method is presented to find the global optimal solution, and as an alternative, a successive convex approximation (SCA)-based method with arithmetic and geometric means (AGM) inequality is designed to achieve the suboptimal solution with low complexity. Moreover, in a special case with single transmit antenna, the closed-form expression of the optimal power allocation is derived for a given power splitting (PS) ratio and then the global optimal solution is found by using Bisection method. For the CDI case, the first-order Taylor expansion is adopted to approximate the non-convex constraints and then a SCA-based algorithm is designed to find the suboptimal solution. Numerical results validate our obtained theoretical results and proposed solution methods, and also show that by migrating FD relaying into SWIPT-enabled cooperative NOMA, a considerable system performance gain can be achieved for both full CSI and CDI cases. Besides, we also discuss the gain brought by NOMA and FD separately and the effect of the relay location on the system performance. It shows that FD may bring more contribution to the system performance improvement than NOMA.

Considering that wireless unidirectional full-duplex (FD) transmission is one of the FD transmissions over 5G mobile wireless networks, this paper proposes a joint receive and transmit relay beamformer design for systems consisting of a source, a FD relay, an intended destination, and an eavesdropper. The source and destination are single-antenna nodes, whereas the FD relay is a multi-antenna node. Assuming that full channel state information (CSI) is available and the eavesdropper processes two blocks of received data at a time, the joint optimization problem is reformulated as a semidefinite relaxation (SDR) problem (in terms of relay transmit beamformer), which is tight in the sense that the rank-one beamformer can always be recovered from the SDR solution. In order to significantly minimize the computational cost of the SDR implementation, a novel semi-analytical approach based on dual optimization is proposed to obtain the optimum transmit beamformer. When the number of data blocks is arbitrary, we propose a successive convex approximation approach for solving the original non-convex optimization problem and show that a stationary solution can be efficiently obtained. We then propose a distributionally robust beamformer design for the case of an arbitrary number of blocks, assuming that the means and covariance matrices of the eavesdropper's channels are known. Computer simulations show that the proposed semi-analytical solution matches with that obtained from numerical optimization of the SDR problem, the FD scheme significantly outperforms its half-duplex counterpart, and the proposed robust design provides robustness against CSI uncertainty.

Media-based modulation (MBM) is a recently proposed modulation scheme which uses radio frequency (RF) mirrors at the transmit antenna(s) in order to create different channel fade realizations based on their ON/OFF status. These complex fade realizations constitute the modulation alphabet. MBM has the advantage of increased spectral efficiency and performance. In this paper, we investigate the performance of some physical layer techniques when applied to MBM. Particularly, we study the performance of $i)$ MBM with generalized spatial modulation (GSM), $ii)$ MBM with mirror activation pattern (MAP) selection based on an Euclidean distance (ED) based metric, and $iii)$ MBM with feedback based phase compensation and constellation rotation. Our results show that, for the same spectral efficiency, GSM-MBM can achieve better performance compared to MIMO-MBM. Also, it is found that MBM with ED-based MAP selection results in improved bit error performance, and that phase compensation and MBM constellation rotation increases the ED between the MBM constellation points and improves the performance significantly. We also analyze the diversity orders achieved by the ED-based MAP selection scheme and the phase compensation and constellation rotation (PC-CR) scheme. The diversity orders predicted by the analysis are validated through simulations.

Media-based modulation (MBM) is a recently proposed modulation scheme which uses radio frequency (RF) mirrors at the transmit antenna(s) in order to create different channel fade realizations based on their ON/OFF status. These complex fade realizations constitute the modulation alphabet. MBM has the advantage of increased spectral efficiency and performance. In this paper, we investigate the performance of some physical layer techniques when applied to MBM. Particularly, we study the performance of i) MBM with generalized spatial modulation (GSM), ii) MBM with mirror activation pattern (MAP) selection based on an Euclidean distance (ED) based metric, and iii) MBM with feedback based phase compensation and constellation rotation. Our results show that, for the same spectral efficiency, GSM-MBM can achieve better performance compared to MIMO-MBM. Also, it is found that MBM with ED-based MAP selection results in improved bit error performance, and that phase compensation and MBM constellation rotation increases the ED between the MBM constellation points and improves the performance significantly.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper addresses the problem of source and relay transmit covariance optimization on the Gaussian MIMO relay channel with full channel state information (CSI), i.e., assuming perfect knowledge of all channels. For full-duplex relaying, we show that the cut-set bound on capacity can be computed as the solution of a convex problem, thus providing a tighter bound than previously published. For time division duplex (TDD) relaying, both upper and lower bounds on capacity are derived, and the transmit covariance matrices are optimized for decode-and-forward (DF) strategies with either partial or full decoding at the relay. A generic procedure is introduced to formulate these problems into a standard convex form, and to solve them efficiently. Suboptimum precoders are also proposed which have a specific matrix structure that either leads to a closed-form expression or at least reduces the dimension of the optimization problem. Practical aspects related to transmit power constraints and CSI availability are then discussed. Finally, simulations in a cellular downlink scenario show that the partial DF strategy can achieve a rate very close to capacity for realistic values of the source to relay SNR, and that the rate loss due to suboptimum precoder structures remains small for typical antenna configurations. </para>

This paper studies power allocation for performance constrained dual-hop variable-gain amplify-and-forward (AF) relay networks in Nakagami- m fading. In this context, the performance constraint is formulated as a constraint on the end-to-end signal-to-noise-ratio (SNR) and the overall power consumed is minimized while maintaining this constraint. This problem is considered under two different assumptions of the available channel state information (CSI) at the relays, namely full CSI at the relays and partial CSI at the relays. In addition to the power minimization problem, we also consider the end-to-end SNR maximization problem under a total power constraint for the partial CSI case. We provide closed-form solutions for all the problems which are easy to implement except in two cases, namely selective relaying with partial CSI for power minimization and SNR maximization, where we give the solution in the form of a one-variable equation which can be solved efficiently. Numerical results are then provided to characterize the performance of the proposed power allocation algorithms considering the effects of channel parameters and CSI availability.

In this paper, we introduce and analyze the performance of a two-hop three-node full-duplex (FD) relay network, where the source and relay nodes transmit using media-based modulation (MBM). An MBM is a promising new modulation scheme that conveys information bits by digitally controlling the parasitic elements (known as radio frequency mirrors) placed near the transmit antenna. The relay uses decode-and-forward relaying protocol. We refer to this system as FD relaying system with MBM (FDR-MBM). We first derive an upper bound on the end-to-end average bit error probability of FDR-MBM with maximum-likelihood detection at the relay and destination nodes. The bound is increasingly tight with increasing signal-to-noise ratios. Numerical results show that, for the same spectral efficiency, FDR-MBM can perform better than FD relaying using conventional modulation schemes. We then derive the diversity order achieved in FDR-MBM. The analytically predicted diversity orders are validated through simulations. Finally, we derive lower and upper bounds on the achievable rate in FDR-MBM.

In this paper three different techniques to predict the channel transfer functions of non flat fading channels in multiple antenna systems are investigated. The prediction is done into time direction. In time division duplex systems, it is beneficial to have the full channel state information. A receiver can achieve the channel state information for one certain time instant based on the reception of a-priori known training signals. This estimated channel state information can be outdated when receiving signals at another time instant or especially when transmitting a signal back to the previously transmitter at another time instant. One possibility to cope with the problem of outdated channel state information is to retransmit a-priori known training signals in order to update the channel state information but this decreases the spectral efficiency. This paper shows techniques to perform the prediction based on the estimation of the physical path parameters of the electromagnetic waves and based on filtering the outdated channel state information. The performance of the presented techniques is evaluated by means of measurement results.

This paper presents a new framework for designing decentralized rank-1 pre-coders in MIMO interference channel. The proposed pre-coders aim to separate the received signal points corresponding to different bits into distinct clusters at every receiver. This is accomplished by minimizing the overlaps between conditional probability density functions (PDFs) given the sent bits, which is shown to be equivalent to maximizing the weighted Euclidean distance between the signal points. This formulation is shown to be synonymous to minimizing an upper bound to the probability of error or maximizing the approximated Bhattacharya distances of the conditional PDFs. When full channel state information (CSI) is given at all transmitters and receivers, our design is shown to offer significant performance gain over a wide range of SNR when compared to other pre-coder designs in the literature. We also extend our pre-coder design to the case when transmitters only have partial CSI in an arbitrary form. When the partial CSI is given in the form of quantized levels of channel coefficients, our design is shown to retain considerable performance gain as we partition the channel coefficients with finer resolutions.

The Rayleigh flat fading channel at low SNR is considered. With full channel state information (CSI) at the transmitter and receiver, its capacity is shown to be essentially SNR log(1SNR) nats/symbol, as SNR goes to zero. In fact, this rate can be achieved with a just one bit of CSI at the transmitter (per fading realization) and with no receiver CSI. The capacity for the case of noisy transmitter CSI is also found. Then a Rayleigh block fading channel of coherence interval T ≤ 1/ SNR is considered which has causal feedback and no a priori CSI. A training based scheme is proposed for such channels, which achieves a rate of SNR logT nats/symbol in the limit of small SNR and large T. Thus, when coherence interval T is of the order 1/SNR, without any a priori CSI at either end, the capacity with full CSI at both ends is achievable. For smaller values of T, a rate of SNR logT nats/symbol is shown to be achievable.

Compressive sensing based multiuser detector for massive MBM MIMO uplink

The idea of media-based modulation (MBM), introduced in [1] [2], is to embed information in the variations of the transmission media (channel states). This is in contrast to legacy wireless systems which embeds data in a radio frequency (RF) source prior to the transmit antenna. MBM offers several advantages over legacy systems, including “additivity of information over multiple receive antennas” and “inherent diversity over a static fading channel”. MBM is particularly suitable for transmitting high data rates using a single transmit unit and multiple receive antennas (single input multiple output MBM, or SIMO-MBM). Furthermore, layered multiple input multiple output MBM (LMIMO-MBM) [3] addresses hardware and decoding complexity along with training overhead when transmitting high data rates using a single MBM transmit unit. The current article compares the performance of MBM and LMIMO-MBM vs. legacy multiple input multiple output (MIMO) and emerging modulation techniques, spatial modu-lation (SM), and its variants, such as generalized SM (GSM) and quadrature SM (QSM). These comparisons demonstrate considerable performance gains for MBM and LMIMO-MBM vs. these notable schemes.

This paper considers a scenario in which multiple device-to-device (D2D) users can reuse the uplink resources of a cellular network to transmit directly to their corresponding receivers. The aggregated interference from the D2D users is limited by applying a threshold on the allowable interference in the base station. The problem is solved under two types of constraints, namely, the peak interference and average interference constraints. In the former, we assume that full channel state information (CSI) is available at the base station, and we optimize the allowable transmit power for the D2D users so that the number of coexisting D2D communications is maximized. We further define a quality-of-service constraint for the D2D users. In practice, however, it is difficult to have complete CSI at the base station as it imposes heavy signaling overhead. Therefore, in the latter scenario, we assume that no knowledge about the location of D2D users and their CSI are available at the base station. This approach does not impose any signaling overhead. Our results show that even with no CSI knowledge, we are able to improve the system performance in terms of throughput by allowing coexisting D2D communications while satisfying the cellular user's constraints.

We consider a wireless base station serving L users through L time-varying channels. It is well known that opportunistic scheduling algorithms with full channel state information (CSI) can stabilize the system and achieve the full capacity region. However, opportunistic scheduling algorithms with full CSI may not be energy efficient when the cost of channel acquisition is high and traffic rates are low. In particular, under the low traffic rate regime, it may be sufficient and more energy-efficient to transmit data with no CSI, i.e., to transmit data blindly, since no power for channel acquisition is consumed. In general, we show that purely channel-aware or purely channel-blind strategies are not necessarily optimal, and we must consider mixed strategies. We derive a unified scheduling algorithm that dynamically chooses to transmit data with full or no CSI based on queue backlog and channel statistics. Through Lyapunov analysis, we show that the unified algorithm can stabilize the downlink with optimal power consumption.

In a single-input single-output (SISO) downlink with multiple users, to obtain the multiuser diversity gain, the full channel state information (CSI) for all users is required for selecting the 'best' user and transmission mode. However, feedback channels are often capable of carrying only a limited number of bits. With such rate-limited feedback links, we intend to maximize the sum-rate of systems with average power and bit-error rate (BER) constraints by varying the transmission mode according to feedback information. Althrough in multiuser systems with finite-rate feedback, the scheduled user is not necessarily the 'best' user, this work turns out to be a design of transmission modes based on CSI of the 'best' user. A nested iterative algorithm is proposed to obtain optimal thresholds and discrete transmission modes. Simulation results demonstrate the throughput with finite-rate feedback approaches that with perfect CSI when the feedback rate increases. As the number of users increases, the multiuser diversity gain is achieved and the average feedback load is reduced without the decrease of throughput.