Emerging wireless communication systems will be characterized by a tight coupling between communication and positioning. This is particularly apparent in millimeter-wave (mm-wave) communications, where devices use a large number of antennas, and the propagation is well described by geometric channel models. For mm-wave communications, initial access, consisting in the beam selection and alignment of two devices, is challenging and time consuming in the absence of location information. Conversely, accurate positioning relies on high-quality communication links with proper beam alignment. This paper studies this interaction and proposes a new position-aided transmitter beam selection protocol, which considers the problem of joint communication and positioning in scenarios with direct line-of-sight and scattering. Simulation results show significant reductions in latency with respect to a standard protocol.

Massive multiple-input multiple-output (MIMO) theoretical performance results have attracted the attention of the community due to the possibility of increasing the spectral efficiency in wireless communications. The performance potential is mainly conditioned to the use of digital beamforming techniques which demand one radio-frequency (RF) chain per antenna element. For large arrays, this implementation may result in high complexity, power consumption, and cost. To reduce the number of RF chains, we use a hybrid beamforming (HB) architecture of an analog beamformer implemented by using phase-shifters and a low-dimensional digital beamformer. The performance of the HB depends on the resolution of the phase-shifters. However, very few works in the literature take into account finite phase-shifters. In this paper, we address the problem of designing HB in frequency selective channels using finite-resolution phase-shifters. The strategy is to exploit the second-order statistics of the channel and a least-square formulation to obtain the discrete phase of each phase-shifter. The digital part is derived based on analog solution to maximize the single-user MIMO system sum-rate. This solution requires a number of RF chains compared to the rank of the spatial covariance matrix which is far lower than ones demanded to implement the full digital beamforming. The simulation results show that the proposed technique can achieve a sum-rate performance very close to that of the digital beamforming assuming low-rank channels.

The performance of massive multiple input multiple output systems may be limited by inter-cell pilot contamination (PC) unless appropriate PC mitigation or avoidance schemes are employed. In this paper we develop techniques based on existing long term evolution (LTE) measurements - open loop power control (OLPC) and pilot sequence reuse schemes, that avoid PC within a group of cells. We compare the performance of simple least-squares channel estimator with the higher-complexity minimum mean square error estimator, and evaluate the performance of the recently proposed coordinated pilot allocation (CPA) technique (which is appropriate in cooperative systems). The performance measures of interest include the normalized mean square error of channel estimation, the downlink signal-to-interference-plus-noise and spectral efficiency when employing maximum ratio transmission or zero forcing precoding at the base station. We find that for terminals moving at vehicular speeds, PC can be effectively mitigated in an operation and maintenance node using both the OLPC and the pilot reuse schemes. Additionally, greedy CPA provides performance gains only for a fraction of terminals, at the cost of degradation for the rest of the terminals and higher complexity. These results indicate that in practice, PC may be effectively mitigated without the need for second-order channel statistics or inter-cell cooperation.

We consider a wireless network comprising a number of cochannel (hence mutually interfering) links. We study the power control problem of maximizing the rate that all links can simultaneously support under a novel setup, where receivers have interference cancelation (IC) capabilities. The problem of allocating the transmitting power is intertwined with determining the links on which receivers can perform IC and the order of cancelations. We provide and prove the theoretical results of the problem complexity and structural properties. For the problem solution, we propose a mixed-integer linear programming framework that enables jointly determining the optimal power and the IC patterns using off-the-shelf algorithms. This allows for the accurate assessment of the potential of IC for power control. Extensive numerical results are presented for performance evaluation, demonstrating the benefit of deploying IC in power control.

The downlink of multicell orthogonal frequency‐division multiple‐access (OFDMA) networks is studied, and the adaptive allocation of spectrum, power and rate is addressed. The authors consider networks with adaptive frequency reuse and discrete‐level rates. Initially, the joint allocation problem is formulated as a centralised non‐linear mixed‐integer program (MIP), which is computationally intractable to solve optimally for practical problem sizes. Then, the capability of the receivers is exploited to estimate the subcarrier channel gains and the joint allocation problem is accordingly decomposed into subproblems, each of which is solved by a different base station with linear complexity. In the proposed iterative algorithm, the base stations perform rate and receiver allocation per subcarrier, with concurrent iterations. A filtering method is introduced to further decrease the algorithm complexity. Furthermore, for benchmarking purposes, the authors transform the original non‐linear MIP to a linear MIP and find the optimal solution by means of standard branch‐and‐cut solvers. The merit of the proposed algorithm is demonstrated with numerical comparisons of its performance against the solutions of the linear MIP and the iterative waterfilling algorithm.

We assess the system-level performance of non-orthogonal spectrum sharing achieved via maximum sum-rate (SR), Nash bargaining (NB), and zero-forcing (ZF) transmit beamforming techniques. A look-up table based physical layer abstraction and radio resource management mechanisms (including packet scheduling) are proposed and incorporated in system-level simulations, jointly with other important aspects of network operation. In the simulated scenarios, the results show similar system-level performance of SR (or NB) as ZF in the context of spectrum sharing, when combined with maximum sum-rate (or proportional fair) packet scheduler. Further sensitivity analysis also shows similar behavior of all three beamforming techniques with regard to the impact on system-level performance of neighbor-cell activity level and feedback error. A more important observation from our results is that, under ideal conditions, the performance enhancement of non-orthogonal spectrum sharing over orthogonal spectrum sharing and fixed spectrum assignment is significant.

We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.

We consider a wireless network comprising a number of mutually-interfering links. We study the transmit power control problem that determines the egalitarian signal-to-interference-plus-noise ratio under a novel setup. Namely, we assume that the receivers have multiuser detection capability, which enables decoding and cancellation of the interference, when it is strong enough. Determining the interference terms that can be cancelled is a combinatorial problem, which is intertwined with the power control problem. We propose a mixed-integer linear programming framework that jointly solves these problems optimally, using off-the-shelf algorithms. We illustrate with a simulation result the merit of the novel approach against the conventional one that precludes interference cancellation.

In this paper, we study an achievable rate region of the two-user multiple-input single-output (MISO) interference channel. We find the transmit beamforming vectors that achieve Pareto-optimal points. We do so, by deriving a sufficient condition for Pareto optimality. Given the beamforming vector of one transmitter, this condition enables us to determine the beamforming vector of the other transmitter that forms a Pareto-optimal pair. The latter can be done in closed form by solving a cubic equation. The result is validated against state-of-the-art methods via numerical illustrations.

The computational complexity of optimum decoding for an orthogonal space-time block code GNsatisfying GNHGN= c(Σk=1K|sk|2)INwhere c is a positive integer is quantified. Four equivalent techniques of optimum decoding which have the same computational complexity are specified. Modifications to the basic formulation in special cases are calculated and illustrated by means of examples. This paper corrects and extends, and unifies them with the results from the literature. In addition, a number of results from the literature are extended to the case c >; 1.

The computational complexity of optimum decoding for an orthogonal space-time block code is quantified. Four equivalent techniques of optimum decoding which have the same computational complexity are specified. Modifications to the basic formulation in special cases are calculated and illustrated by means of examples.

We consider the problem of transmit beamforming to multiple co-channel multicast groups. Since the direct minimization of transmit power while guaranteeing a prescribed minimum signal to interference plus noise ratio (SINR) at each receiver is nonconvex and NP-hard, we present convex SDP relaxations of this problem and study when such relaxations are tight. Our results show that when the steering vectors for all receivers are of Vandermonde type (such as in the case of a uniform linear array and line-of-sight propagation), a globally optimum solution to the corresponding transmit beamforming problem can be obtained via an equivalent SDP reformulation. We also present various robust formulations for the problem of single-group multicasting, when the steering vectors are only approximately known. Simulation results are presented to illustrate the effectiveness of our SDP relaxations and reformulations.

In this paper pilot aided channel estimation (PACE) for OFDM is addressed. For PACE equidistantly spaced pilot symbols allow to reconstruct the channel response by means of interpolation. The optimum minimum mean squared error (MMSE) estimator performs smoothing and interpolation jointly. To reduce the complexity of the optimum MMSE estimator, we propose to separate the smoothing and interpolation tasks. The separated smoothing and interpolation estimator (SINE) consists of a MMSE based smoother which only operates at the received pilot symbols, and an interpolator which is independent of the channel statistics. We show that the separated approach gets close to the optimum MMSE, while the complexity is grossly reduced. However, at high SNR an error floor is observed, which is caused by edge effects, i.e. subcarriers near the beginning and end of the band suffer from an increased interpolation error.

We assess the capacity potential of very short very-high data-rate digital subscriber line loops using full-binder channel measurements collected by France Telecom R&D. Key statistics are provided for both uncoordinated and vectored systems employing coordinated transmitters and coordinated receivers. The vectoring benefit is evaluated under the assumption of transmit precompensation for the elimination of self-far-end crosstalk, and echo cancellation of self-near-end crosstalk. The results provide useful bounds for developers and providers alike.