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In this paper, we consider a spatial modulation (SM)-based multiple-input–single-output (MISO) system relying on a single radio-frequency chain equipped with a finite-rate feedback channel to provide quantized channel state information (CSI) to the transmitter. First, under the assumption of Rayleigh flat-fading channels and perfect CSI at the transmitter (CSIT), we analyze the symbol error probability (SEP) of an SM scheme, which perfectly compensates the channel phase and employs constellation rotation at the different transmit antennas (TAs). Then, we consider a more practical scenario, where scalar quantization of the channel phase angles is employed, and the quantized CSI is made available to the transmitter via a finite-rate feedback channel. We analyze the SEP reduction, i.e., Pe_L, relative to perfect CSIT, imposed by the quantized CSIT (Q-CSIT). We show that at a high feedback rate, Pe_L varies as C^\prime\mbox2^-2B, where each channel phase angle is quantized to B bits, and C^{\prime} is a constant. Furthermore, based on the rotational symmetry of the M-ary phase-shift keying ( M-PSK) signal constellation, we propose a novel feedback scheme, which requires (n_t-\mbox{1})\log_2(M) fewer bits of feedback with any performance erosion, where n_t$ is the number of TAs. We characterize the performance of the SM-MISO system with finite-rate feedback and validate our analysis through Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we present novel precoding methods for multiuser Rayleigh fading multiple-input–multiple-output (MIMO) systems when channel state information (CSI) is available at the transmitter (CSIT) but not at the receiver (CSIR). Such a scenario is relevant, for example, in time-division duplex (TDD) MIMO communications, where, due to channel reciprocity, CSIT can be directly acquired by sending a training sequence from the receiver to the transmitter(s). We propose three transmit precoding schemes that convert the fading MIMO channel into a fixed-gain additive white Gaussian noise (AWGN) channel while satisfying an average power constraint. We also extend one of the precoding schemes to the multiuser Rayleigh fading multiple-access channel (MAC), broadcast channel (BC), and interference channel (IC). The proposed schemes convert the fading MIMO channel into fixed-gain parallel AWGN channels in all three cases. Hence, they achieve an infinite diversity order, which is in sharp contrast to schemes based on perfect CSIR and no CSIT, which, at best, achieve a finite diversity order. Further, we show that a polynomial diversity order is retained, even in the presence of channel estimation errors at the transmitter. Monte Carlo simulations illustrate the bit error rate (BER) performance obtainable from the proposed precoding scheme compared with existing transmit precoding schemes. [ABSTRACT FROM PUBLISHER]

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

This paper considers the design of a power-controlled reverse channel training (RCT) scheme for spatial multiplexing (SM)-based data transmission along the dominant modes of the channel in a time-division duplex (TDD) multiple-input and multiple-output (MIMO) system, when channel knowledge is available at the receiver. A channel-dependent power-controlled RCT scheme is proposed, using which the transmitter estimates the beamforming (BF) vectors required for the forward-link SM data transmission. Tight approximate expressions for 1) the mean square error (MSE) in the estimate of the BF vectors, and 2) a capacity lower bound (CLB) for an SM system, are derived and used to optimize the parameters of the training sequence. Moreover, an extension of the channel-dependent training scheme and the data rate analysis to a multiuser scenario with M user terminals is presented. For the single-mode BF system, a closed-form expression for an upper bound on the average sum data rate is derived, which is shown to scale as ((Lc - LB, \tau)/Lc) \log \log M asymptotically in M, where Lc and LB, \tau are the channel coherence time and training duration, respectively. The significant performance gain offered by the proposed training sequence over the conventional constant-power orthogonal RCT sequence is demonstrated using Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problem of channel estimation in a single cell massive multiple-input multiple-output (mMIMO) system with distributed antenna arrays (DAA) under the availability of limited pilots. Specifically, we propose to use pilots that are not only orthogonal within a cluster but also minimally correlated across clusters. We show that pilot sets that form mutually unbiased orthonormal bases (MUOB) minimize both inter- and intra-cluster pilot contamination. This also allows us to optimally choose the number of pilots needed to serve a given number of user equipments (UEs) within a DAA-mMIMO system. Following this, we develop an access point (AP) centered UE clustering algorithm to optimally cluster UEs for MUOB pilot allocation. Our experiments reveal that in a DAA-mMIMO system, MUOB not only offers better fairness compared to the traditional orthogonal pilot reuse scheme in terms of channel estimation error and per-UE throughput, but also delivers a higher sum system throughput. [ABSTRACT FROM AUTHOR]

A design methodology based on the minimum error probability (MEP) framework is proposed for a nonregenerative multiple-input multiple-output relay-aided system. We consider the associated cognitive, the parallel, and the multihop source–relay-destination link design based on this MEP framework, including the transmit precoder, the amplify-and-forward relay matrix, and the receiver equalizer matrix of our system. It has been shown in the literature that MEP-based communication systems are capable of improving the error probability of other linear counterparts. Our simulation results demonstrate that the proposed scheme indeed achieves a significant bit-error-ratio reduction over the existing linear schemes. [ABSTRACT FROM AUTHOR]