Single-antenna Receivers Research Articles

Transmit Optimization for the MISO Multicast Interference Channel

In this paper, we consider multiple-input single-output (MISO) physical layer multicasting, where several multiantenna transmitters each simultaneously multicast a common message to a distinct set of single-antenna receivers, causing interference between different multicast messages. To optimize the achievable rate of this MISO multicast interference channel, we propose iterative distributed transmit optimization algorithms that are based on interference leakage control, requiring local channel state information at each transmitter and leakage information exchange among transmitters. We, furthermore, propose extensions of existing coordinated multipoint transmission schemes that have been developed for unicast interference channels, such as signal to leakage and noise ratio beamforming, to the considered multicast system. Such methods are of importance, e.g., for future releases of LTE that will support multiantenna multicasting using MBMS/MBSFN. Numerical simulations confirm the potential of the proposed distributed transmit optimization algorithm.

Capacity Region of MISO Broadcast Channel for Simultaneous Wireless Information and Power Transfer

This paper studies a multiple-input–single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer, where a multiantenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID receivers by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC–multiple-access-channel duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms.

Performance Analysis of Cooperative Wireless Networks With Unreliable Backhaul Links

A cooperative wireless network, where a cluster of $K$ single-antenna transmitters jointly serve a single-antenna receiver, is considered. Each transmitter is connected to the control unit (CU) via independent but unreliable backhaul links. The CU sends a common message to each transmitter over backhaul links, which upon successful reception, jointly transmit this message to the intended receiver. To facilitate analysis, a general expression is derived for the complementary cumulative distribution function of a sum of $K$ independent random variables, where each random variable is a product of an exponential and a Bernoulli random variable. This result is applied to find a simple closed-form expression that characterizes the system outage performance as a function of network parameters and node geometry. The analytical model is validated using numerical simulations. As an application, the derived expression is also used for investigating the impact of backhaul assignment on the system performance.

Multistatic target tracking for passive radar in a DAB/DVB network: initiation

A passive radar system that coopts digital broadcast (DAB/ DVB) signals is appealing but challenging: a single-antenna receiver system can only measure a bistatic range/range-rate; and, due to the energy-efficient multitransmitter commercial implementation, there is a confounding uncertainty as to which transmitter (illuminator) was responsible for a given “hit.” In a companion paper we proposed some ways to track directly in native geographic coordinates. Here we suggest and compare two approaches for track initiation.

Artificial-Noise-Aided Secure Multi-Antenna Transmission With Limited Feedback

We present an optimized secure multi-antenna transmission approach based on artificial-noise-aided beamforming, with limited feedback from a desired single-antenna receiver. To deal with beamformer quantization errors as well as unknown eavesdropper channel characteristics, our approach is aimed at maximizing throughput under dual performance constraints-a connection outage constraint on the desired communication channel and a secrecy outage constraint to guard against eavesdropping. We propose an adaptive transmission strategy that judiciously selects the wiretap coding parameters, as well as the power allocation between the artificial noise and the information signal. This optimized solution reveals several important differences with respect to solutions designed previously under the assumption of perfect feedback. We also investigate the problem of how to most efficiently utilize the feedback bits. The simulation results indicate that a good design strategy is to use approximately 20% of these bits to quantize the channel gain information, with the remainder to quantize the channel direction, and this allocation is largely insensitive to the secrecy outage constraint imposed. In addition, we find that 8 feedback bits per transmit antenna is sufficient to achieve approximately 90% of the throughput attainable with perfect feedback.

Blind Interference Alignment for Cellular Networks

We propose a blind interference alignment scheme for partially connected cellular networks. The scheme cancels both intracell and intercell interference by relying on receivers with one reconfigurable antenna and by allowing users at the cell edge to be served by all the base stations in their proximity. An outer bound for the degrees of freedom is derived for general partially connected networks with single-antenna receivers when knowledge of the channel state information at the transmitter is not available. It is demonstrated that for symmetric scenarios, this outer bound is achieved by the proposed scheme. On the other hand, for asymmetric scenarios, the achievable degrees of freedom are not always equal to the outer bound. However, the penalty is typically small, and the proposed scheme outperforms other blind interference alignment schemes. Moreover, significant reduction of the supersymbol length is achieved compared with a standard blind interference alignment strategy designed for fully connected networks.

Joint Beamforming and Power Splitting for MISO Interference Channel With SWIPT: An SOCP Relaxation and Decentralized Algorithm

This paper considers a power splitting-based MISO interference channel for simultaneous wireless information and power transfer (SWIPT), where each single antenna receiver splits the received signal into two streams of different power for decoding information and harvesting energy separately. We aim to minimize the total transmission power by joint beamforming and power splitting (JBPS) under both the signal-to-interference-plus-noise ratio (SINR) constraints and energy harvesting (EH) constraints. The JBPS problem is nonconvex and has not yet been well addressed in the literature. Moreover, decentralized algorithm design for JBPS based on local channel state information (CSI) and limited information exchange remains open. In this paper, we first propose a novel relaxation method named second-order cone programming (SOCP) relaxation to address the JBPS problem. We formulate the relaxed problem as an SOCP and present two sufficient conditions under which the SOCP relaxation is tight. For the case when the SOCP solution is not necessarily optimal to the JBPS problem, a closed-form feasible-solution-recovery method is provided. Then, we develop a distributed algorithm for the JBPS problem based on primal-decomposition (PD) method. The PD-based distributed algorithm consists of a master problem and a set of subproblems. The former is solved by using subgradient method while the latter are solved using coordinate descent method. Finally, numerical results validates the efficiency of the proposed algorithms.

An Eigen Approach to Transmit Beamforming in Wireless Networks With Single Antenna Receivers

In this paper, we propose an eigen framework for transmit beamforming for single-hop and dual-hop network models with single antenna receivers. In cases where number of receivers is not more than three, the proposed Eigen approach is vastly superior in terms of ease of implementation and computational complexity compared with the existing convex-relaxation-based approaches. The essential premise is that the precoding problems can be posed as equivalent optimization problems of searching for an optimal vector in the joint numerical range of Hermitian matrices. We show that the latter problem has two convex approximations: the first one is a semi-definite program that yields a lower bound on the solution, and the second one is a linear matrix inequality that yields an upper bound on the solution. We study the performance of the proposed and existing techniques using numerical simulations.

Joint Opportunistic Beam and Spectrum Selection Schemes for Spectrum Sharing Systems With Limited Feedback

Spectrum sharing systems have been introduced to alleviate the problem of spectrum scarcity by allowing an unli- censed secondary user (SU) to share the spectrum with a licensed primary user (PU) under acceptable interference levels to the primary receiver (PU-Rx). In this paper, we consider a secondary link composed of a secondary transmitter (SU-Tx) equipped with multiple antennas and a single-antenna secondary receiver (SU-Rx). The secondary link is allowed to share the spectrum with a primary network composed of multiple PUs communicating over distinct frequency spectra with a primary base station. We develop a transmission scheme where the SU-Tx initially broadcasts a set of random beams over all the available primary spectra for which the PU-Rx sends back the index of the spectrum with the minimum interference level, as well as information that describes the inter- ference value, for each beam. Based on the feedback information on the PU-Rx, the SU-Tx adapts the transmitted beams and then resends the new beams over the best primary spectrum for each beam to the SU-Rx. The SU-Rx selects the beam that maximizes the received signal-to-interference-plus-noise ratio (SINR) to be used in transmission over the next frame. We consider three cases for the level of feedback information describing the interference level. In the first case, the interference level is described by both its magnitude and phase; in the second case, only the magnitude is considered; and in the third case, we focus on a q-bit description of its magnitude. In the latter case, we propose a technique to find the optimal quantizer thresholds in a mean-square-error sense. We also develop a statistical analysis for the SINR statistics and the capacity and bit error rate of the secondary link and present numerical results that study the impact of the different system parameters.

Multiuser MISO Beamforming for Simultaneous Wireless Information and Power Transfer

Simultaneous wireless information and power transfer (SWIPT) is anticipated to have abundant applications in future machine or sensor based wireless networks by providing wireless data and energy access at the same time. In this paper, we study a multiuser multiple-input single-output (MISO) broadcast SWIPT system, where a multi-antenna access point (AP) sends information and energy simultaneously via spatial multiplexing to multiple single-antenna receivers each of which implements information decoding (ID) or energy harvesting (EH). Since EH receivers in practice operate with considerably higher received power than ID receivers, we propose a receiver location based transmission scheduling, where receivers that are close to the AP are scheduled for EH while those more distant from the AP for ID. We aim to maximize the weighted sum-power transferred to all EH receivers subject to a given set of minimum signal-to-interference-and-noise ratio (SINR) constraints at different ID receivers. In particular, we consider two types of ID receivers (referred to as Type I and Type II, respectively) without or with the capability of cancelling the interference from (a priori known) energy signals. For each type of ID receivers, we formulate the joint information and energy transmit beamforming design as a non-convex quadratically constrained quadratic program (QCQP). First, we obtain the globally optimal solutions for our formulated QCQPs by applying an optimization technique so-called semidefinite relaxation (SDR). It is shown via SDR that no dedicated energy beam is needed for Type I ID receivers to achieve the optimal solution; while for Type II ID receivers, employing no more than one energy beam is optimal. Next, we establish a new form of the celebrated uplink-downlink duality to develop alternative algorithms to obtain the same optimal solutions as SDR.

Outage Probability Analysis of MIMO Cognitive Radios with Single Transmit and Receive Antenna Selection

For multiple-input multiple-output cognitive radio systems, we propose an optimal single transmit and receive antenna selection scheme which maximizes the signal-to-interference-and-noise ratio. Considering peak interference power constraint, peak transmit power constraint, and interference from primary transmitter to cognitive receiver, we theoretically derive the exact system outage probability. It is shown that the theoretical results match simulation results.

A Novel Mode Switching Scheme Utilizing Random Beamforming for Opportunistic Energy Harvesting

Since radio signals carry both energy and information at the same time, a unified study on simultaneous wireless information and power transfer (SWIPT) has recently drawn a significant attention for achieving wireless powered communication networks. In this paper, we study a multiple-input single-output (MISO) multicast SWIPT network with one multi-antenna transmitter sending common information to multiple single-antenna receivers simultaneously along with opportunistic wireless energy harvesting at each receiver. From the practical consideration, we assume that the channel state information (CSI) is only known at each respective receiver but is unavailable at the transmitter. We propose a novel receiver mode switching scheme for SWIPT based on a new application of the conventional random beamforming technique at the multi-antenna transmitter, which generates artificial channel fading to enable more efficient energy harvesting at each receiver when the received power exceeds a certain threshold. For the proposed scheme, we investigate the achievable information rate, harvested average power and power outage probability, as well as their various trade-offs in quasi-static fading channels. Compared to a reference scheme of periodic receiver mode switching without random transmit beamforming, the proposed scheme is shown to be able to achieve better rate-energy trade-offs when the harvested power target is sufficiently large. Particularly, it is revealed that employing one single random beam for the proposed scheme is asymptotically optimal as the transmit power increases to infinity, and also performs the best with finite transmit power for the high harvested power regime of most practical interests, thus leading to an appealing low-complexity implementation. Finally, we compare the rate-energy performances of the proposed scheme with different random beam designs.

Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

This paper considers the K-user cognitive interference channel with one primary and K-1 secondary/cognitive transmitters with a cumulative message sharing structure, i.e., cognitive transmitter i ϵ [2 : K] has non-causal knowledge of the messages of users with index less than i. A computable outer bound valid for any memoryless channel is proposed. The sum-rate outer bound is evaluated first for the high-SNR linear deterministic approximation of the Gaussian noise channel. This is shown to be both the sum capacity for the 3-user channel with arbitrary channel gains, and the sum-capacity for the symmetric K-user channel. Interestingly, for the K user channel, cognition at transmitters 2 to K-1 is not needed, and knowledge of all messages at the K-th transmitter only is sufficient to achieve the sum-capacity. Next, the sum-capacity of the symmetric Gaussian noise channel is characterized to within a constant additive and multiplicative gap, both of which are functions of K. As opposed to other multiuser interference channel models, a single scheme (in this case based on dirty-paper coding) suffices for both the weak and strong interference regimes. The generalized degrees of freedom (gDoF) are then derived and are shown, unlike interference and broadcast channels, to be a function of K. Interestingly, it is shown that as the number of users grows to infinity the gDoF of the K-user cognitive interference channel with cumulative message sharing tends to the gDoF of a broadcast channel with a K-antenna transmitter and K single-antenna receivers. Finally, numerical evaluations show that the actual gaps between the presented inner and outer bounds are significantly smaller than the analytically derived gaps.

Power Allocation in MISO Interference Channels with Stochastic CSIT

This paper considers multiuser interference channels in which the transmitters have imperfect channel state information (CSI) where CSI perturbations are modeled stochastically. Transmitters are assumed to be equipped with multiple antennas serving single-antenna receivers. Transmitters use pre-designed discrete codebooks for beamforming directions and dynamically (based on the available CSI) select the best set of beamformers from the given codebook. The objective is to perform optimal power allocation to different users while certain quality of service (QoS) guarantees are ensured for the users. Imposed by stochastic CSI uncertainties, guarantees provided for the QoS measures have a stochastic nature too. The primary focus is placed on the interference channels for which two power allocation problems are considered. The first problem minimizes power consumption subject to serving users at certain data rates and the second problem considers max-min rate allocation subject to given power budgets for the transmitters. The core step in formalizing these problems in mathematically tractable forms relies on using Bernstein approximation, which approximates and convexifies the non-convex stochastic guarantees by conservative convex and deterministic counterparts. For solving this resulting convex and deterministic optimization problem, a specialized version of the long-step logarithmic barrier cutting plane (LLBCP) algorithm is used. Effectiveness of the proposed solutions and comparisons with other existing methods are assessed via extensive simulation results.

Joint Switched Multi-Spectrum and Transmit Antenna Diversity for Spectrum Sharing Systems

In spectrum sharing systems, a secondary user (SU) is allowed to share the spectrum with a primary (licensed) network under the condition that the interference observed at the receivers of the primary users (PU-Rxs) is below a predetermined level. In this paper, we consider a secondary network comprised of a secondary transmitter (SU-Tx) equipped with multiple antennas and a single-antenna secondary receiver (SU-Rx) sharing the same spectrum with multiple primary users (PUs), each with a distinct spectrum. We develop transmit antenna diversity schemes at the SU-Tx that exploit the multi-spectrum diversity provided by the existence of multiple PUs so as to optimize the signal-to-noise ratio (SNR) at the SU-Rx. In particular, assuming bounded transmit power at the SU-Tx, we develop switched selection schemes that select the primary spectrum and the SU-Tx transmit antenna that maintain the SNR at the SU-Rx above a specific threshold. Assuming Rayleigh fading channels and binary phase-shift keying (BPSK) transmission, we derive the average bit-error-rate (BER) and average feedback load expressions for the proposed schemes. For the sake of comparison, we also derive a BER expression for the optimal selection scheme that selects the best antenna/spectrum pair that maximizes the SNR at the SU-Rx, in exchange of high feedback load and switching complexity. Finally, we show that our analytical results are in perfect agreement with the simulation results.

A 0.7–2.7-GHz Blocker-Tolerant Compact-Size Single-Antenna Receiver for Wideband Mobile Applications

Passive-mixer-first receivers have recently demonstrated flexible, low-noise, and high-linearity performance. Likewise, capacitive coupling element antennas have been demonstrated to be a viable choice for mobile handset integration. This paper combines these two advances into a single-antenna wideband receiver that achieves a 0.7-2.7-GHz reception band. The compact-size wideband tunable antenna achieves an efficiency of 45%-69% and occupies a volume of 2500 mm3. The front-end integrated circuit achieves an input compression point of +5 dBm with a noise figure of 4 dB while occupying only 0.3 mm2 of active die area. Additionally, an interface impedance study is performed to find the optimal impedances around the passive mixer and to demonstrate the different design tradeoffs of a passive-mixer-first receiver. A local oscillator duty-cycle adjustment circuit and its effect on the receiver performance is also presented.

Wireless Information and Power Transfer: A Dynamic Power Splitting Approach

Energy harvesting is a promising solution to prolong the operation time of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the flat-fading channel, where the receiver has no fixed power supplies and thus needs to replenish energy via WEH from the signals sent by the transmitter. We first consider a SISO (single-input single-output) system where the single-antenna receiver cannot decode information and harvest energy independently from the same signal received. Under this practical constraint, we propose a dynamic power splitting (DPS) scheme, where the received signal is split into two streams with adjustable power levels for information decoding and energy harvesting separately based on the instantaneous channel condition that is assumed to be known at the receiver. We derive the optimal power splitting rule at the receiver to achieve various trade-offs between the maximum ergodic capacity for information transfer and the maximum average harvested energy for power transfer, which are characterized by the boundary of a so-called "rate-energy (R-E)" region. Moreover, for the case when the channel state information is also known at the transmitter, we investigate the joint optimization of transmitter power control and receiver power splitting. The achievable R-E region by the proposed DPS scheme is also compared against that by the existing time switching scheme as well as a performance upper bound by ignoring the practical receiver constraint. Finally, we extend the result for optimal DPS to the SIMO (single-input multiple-output) system where the receiver is equipped with multiple antennas. In particular, we investigate a low-complexity power splitting scheme, namely antenna switching, which achieves the near-optimal rate-energy trade-offs as compared to the optimal DPS.

Multi-Cell Random Beamforming: Achievable Rate and Degrees of Freedom Region

Random beamforming (RBF) is a practically favourable transmission scheme for multiuser multi-antenna downlink systems since it requires only partial channel state information (CSI) at the transmitter. Under the conventional single-cell setup, RBF is known to achieve the optimal sum-capacity scaling law as the number of users goes to infinity, thanks to the multiuser diversity enabled transmission scheduling that virtually eliminates the intra-cell interference. In this paper, we extend the study of RBF to a more practical multi-cell downlink system with single-antenna receivers subject to the additional inter-cell interference (ICI). First, we consider the case of finite signal-to-noise ratio (SNR) at each receiver. We derive a closed-form expression of the achievable sum-rate with the multi-cell RBF, based upon which we show an asymptotic sum-rate scaling law as the number of users goes to infinity. Next, we consider the high-SNR regime and for tractable analysis assume that the number of users in each cell scales in a certain order with the per-cell SNR. Under this setup, we characterize the achievable degrees of freedom (DoF) for the single-cell case with RBF. Then we extend the analysis to the multi-cell RBF case by characterizing the DoF region. It is shown that the DoF region characterization provides useful guideline on how to design a cooperative multi-cell RBF system to achieve optimal throughput tradeoffs among different cells. Furthermore, our results reveal that the multi-cell RBF scheme achieves the "interference-free DoF" region upper bound for the multi-cell system, provided that the per-cell number of users has a sufficiently large scaling order with the SNR. Our result thus confirms the optimality of multi-cell RBF in this regime even without the complete CSI at the transmitter, as compared to other full-CSI requiring transmission schemes such as interference alignment.

Blind Maximum Likelihood Carrier Frequency Offset Estimation for OFDM With Multi-Antenna Receiver

In this paper, based on the maximum likelihood (ML) criterion, we propose a blind carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM) with multi-antenna receiver. We find that the blind ML solution in this situation is quite different from the case of single antenna receiver. As compared to the conventional MUSIC-like CFO searching algorithm, our proposed method not only has the advantage of being applicable to fully loaded systems, but also can achieve much better performance in the presence of null subcarriers. It is demonstrated that the proposed method also outperforms several existing estimators designed for multi-antenna receivers. The theoretical performance analysis and numerical results are provided, both of which demonstrate that the proposed method can achieve the Cramer-Rao bound (CRB) under the high signal-to-noise ratio (SNR) region.

On Cyclostationarity Based Spectrum Sensing Under Uncertain Gaussian Noise

Detection of cyclostationary primary user (PU) signals in colored Gaussian noise for cognitive radio systems is considered based on looking for single or multiple cycle frequencies at single or multiple time lags in the cyclic autocorrelation function (CAF) of the noisy PU signal. We explicitly exploit the knowledge that under the null hypothesis of PU signal absent, the measurements originate from possible colored Gaussian noise with unknown correlation function. Our formulation allows us to simplify the spectrum sensing detector and obviates the need for estimating an unwieldy covariance matrix needed in some prior works. We consider both single and multiple antenna receivers, and both nonconjugate and conjugate CAFs. A performance analysis of the proposed detector is carried out. Supporting simulation examples are provided to demonstrate the efficacy of the proposed approaches and to compare them with some existing approaches. Our proposed approaches are computationally cheaper than the Dandawate-Giannakis and related approaches while having quite similar detection performance for a given false alarm rate.