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In this paper, we analyze the benefits of including downlink pilots in a cell-free massive MIMO system. We derive an approximate per-user achievable downlink rate for conjugate beamforming processing, which takes into account both uplink and downlink channel estimation errors, and power control. A performance comparison is carried out, in terms of per-user net throughput, considering cell-free massive MIMO operation with and without downlink training, for different network densities. We take also into account the performance improvement provided by max-min fairness power control in the downlink. Numerical results show that, exploiting downlink pilots, the performance can be considerably improved in low density networks over the conventional scheme where the users rely on statistical channel knowledge only. In high density networks, performance improvements are moderate., Funding Agencies|European Unions Horizon research and innovation programme [641985]

In high-density low-bitrate Internet-of-Things (IoT) use case of 5G networks, the terminals and sensors are to be of extremely low-cost and low energy-consuming. Typically, the analog-to-digital converters (ADCs) dominate the power-budget of receiver chains, in particular if the quantization resolution is high. Hence, receiver architectures deploying 1-bit ADCs are of high interest towards realizing low-cost, high energy-efficiency device solutions. In this paper, we study the waveform design and optimization for a narrowband low-bitrate massive MISO downlink targeting to achieve rates higher than 1 bits/sec (per real-dimension) where the terminal receivers adopt only simple 1-bit quantization (per real-dimension) with oversampling. In this respect, first we show that for a particular precoder structure, the overall link is equivalent to that of an AWGN SISO with controlled intersymbol interference (ISI). The filter design problem for generating the desired ISI in such SISO links has been studied in previous works, however, the only known method in literature is a computationally demanding brute force search method. As a novel contribution, we develop models and tools that elaborate on the conditions to be satisfied for unique detection and existence of solution for the filter coefficients. Then, as a concrete example, the developed models and tools are utilized to show that in the absence of noise, five-times oversampling is required for unique detection of 16-QAM input alphabet. Building on these findings, we then develop novel algorithms that can efficiently design the filter coefficients. Examples and simulations are provided to elaborate on filter coefficient design and optimization, and to illustrate good SER performance of the MISO link with 1-bit receiver even at SNRs down to 5 dB.

Consider the uplink of a single-cell multiuser MIMO system with a very large number of antennas, M, at the base station (BS) and K single-antenna users. A jamming device equipped with K-J antennas transmitting signals attempts to degrade the transmission between the users and the BS. In this paper, we propose a detection algorithm of the jamming attack as well as a method for its rejection. The proposed results are based on the application of results from random matrix theory. We assume that K and K-J are fixed as M converges to infinity while the coherence interval tau is assumed to be of the same order of magnitude as M

We consider massive multiple input multiple output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) that use zero-forcing (ZF) to combat interference. To perform ZF, large dimensional pseudo-inverses have to be computed. In this paper, we propose a discrete Fourier transform (DFT)-interpolation-based technique where substantially fewer ZF matrix computations have to be done with very little deterioration in data rate compared to computing an exact ZF matrix for every subcarrier. We claim that it is enough to compute the ZF matrix at L(amp;lt;amp;lt; N) selected subcarriers where L is the number of resolvable multipaths and N is the total number of subcarriers and then interpolate. The proposed technique exploits the fact that in the massive MIMO regime, the ZF impulse response consists of L dominant components. We benchmark the proposed method against full inversion, piecewise constant and linear interpolation methods and show that the proposed method achieves a good tradeoff between performance and complexity.

In this paper we consider a time-division duplex cell-free massive multiple-input multiple-output (MIMO) system where many distributed access points (APs) simultaneously serve many users. A normalized conjugate beamforming scheme, which satisfies short-term average power constraints at the APs, is proposed and analyzed taking into account the effect of imperfect channel information. We derive an approximate closed-form expression for the per-user achievable downlink rate of this scheme. We also provide, analytically and numerically, a performance comparison between the normalized conjugate beamforming and the conventional conjugate beamforming scheme in [1] (which satisfies long-term average power constraints). Normalized conjugate beamforming scheme reduces the beamforming uncertainty gain, which comes from the users lack of the channel state information knowledge, and hence, it improves the achievable downlink rate compared to the conventional conjugate beamforming scheme.

Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

Target tracking with ultra-wideband (UWB) signals in indoor environments is a challenging problem due to the presence of multipath and non-line-of-sight conditions (NLOS). A solution to this problem is to use particle filtering (PF), which is able to handle both nonlinear models and non-Gaussian uncertainties that typically appear in the presence of NLOS. In this paper, we compare four different PF variants, that differ in terms of how NLOS measurements are handled. According to our experimental results, based on the measurements from a basement tunnel, multiple features from the UWB impulse response should be used, and the ranging likelihood function should make use of both LOS and NLOS measurements. Standard time-of-arrival (TOA) based methods, even with NLOS rejection, are not good enough. Instead we advocate TOA-based algorithms that can actively mitigate errors due to NLOS., COOPLOC

Target tracking with ultra-wideband (UWB) signals in indoor environments is a challenging problem due to the presence of multipath and non-line-of-sight conditions (NLOS). A solution to this problem is to use particle filtering (PF), which is able to handle both nonlinear models and non-Gaussian uncertainties that typically appear in the presence of NLOS. In this paper, we compare four different PF variants, that differ in terms of how NLOS measurements are handled. According to our experimental results, based on the measurements from a basement tunnel, multiple features from the UWB impulse response should be used, and the ranging likelihood function should make use of both LOS and NLOS measurements. Standard time-of-arrival (TOA) based methods, even with NLOS rejection, are not good enough. Instead we advocate TOA-based algorithms that can actively mitigate errors due to NLOS., COOPLOC

Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

Target tracking with ultra-wideband (UWB) signals in indoor environments is a challenging problem due to the presence of multipath and non-line-of-sight conditions (NLOS). A solution to this problem is to use particle filtering (PF), which is able to handle both nonlinear models and non-Gaussian uncertainties that typically appear in the presence of NLOS. In this paper, we compare four different PF variants, that differ in terms of how NLOS measurements are handled. According to our experimental results, based on the measurements from a basement tunnel, multiple features from the UWB impulse response should be used, and the ranging likelihood function should make use of both LOS and NLOS measurements. Standard time-of-arrival (TOA) based methods, even with NLOS rejection, are not good enough. Instead we advocate TOA-based algorithms that can actively mitigate errors due to NLOS., COOPLOC

Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

We consider massive multiple input multiple output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) that use zero-forcing (ZF) to combat interference. To perform ZF, large dimensional pseudo-inverses have to be computed. In this paper, we propose a discrete Fourier transform (DFT)-interpolation-based technique where substantially fewer ZF matrix computations have to be done with very little deterioration in data rate compared to computing an exact ZF matrix for every subcarrier. We claim that it is enough to compute the ZF matrix at L(amp;lt;amp;lt; N) selected subcarriers where L is the number of resolvable multipaths and N is the total number of subcarriers and then interpolate. The proposed technique exploits the fact that in the massive MIMO regime, the ZF impulse response consists of L dominant components. We benchmark the proposed method against full inversion, piecewise constant and linear interpolation methods and show that the proposed method achieves a good tradeoff between performance and complexity.

In high-density low-bitrate Internet-of-Things (IoT) use case of 5G networks, the terminals and sensors are to be of extremely low-cost and low energy-consuming. Typically, the analog-to-digital converters (ADCs) dominate the power-budget of receiver chains, in particular if the quantization resolution is high. Hence, receiver architectures deploying 1-bit ADCs are of high interest towards realizing low-cost, high energy-efficiency device solutions. In this paper, we study the waveform design and optimization for a narrowband low-bitrate massive MISO downlink targeting to achieve rates higher than 1 bits/sec (per real-dimension) where the terminal receivers adopt only simple 1-bit quantization (per real-dimension) with oversampling. In this respect, first we show that for a particular precoder structure, the overall link is equivalent to that of an AWGN SISO with controlled intersymbol interference (ISI). The filter design problem for generating the desired ISI in such SISO links has been studied in previous works, however, the only known method in literature is a computationally demanding brute force search method. As a novel contribution, we develop models and tools that elaborate on the conditions to be satisfied for unique detection and existence of solution for the filter coefficients. Then, as a concrete example, the developed models and tools are utilized to show that in the absence of noise, five-times oversampling is required for unique detection of 16-QAM input alphabet. Building on these findings, we then develop novel algorithms that can efficiently design the filter coefficients. Examples and simulations are provided to elaborate on filter coefficient design and optimization, and to illustrate good SER performance of the MISO link with 1-bit receiver even at SNRs down to 5 dB.

Consider the uplink of a single-cell multiuser MIMO system with a very large number of antennas, M, at the base station (BS) and K single-antenna users. A jamming device equipped with K-J antennas transmitting signals attempts to degrade the transmission between the users and the BS. In this paper, we propose a detection algorithm of the jamming attack as well as a method for its rejection. The proposed results are based on the application of results from random matrix theory. We assume that K and K-J are fixed as M converges to infinity while the coherence interval tau is assumed to be of the same order of magnitude as M

In this paper, we analyze the benefits of including downlink pilots in a cell-free massive MIMO system. We derive an approximate per-user achievable downlink rate for conjugate beamforming processing, which takes into account both uplink and downlink channel estimation errors, and power control. A performance comparison is carried out, in terms of per-user net throughput, considering cell-free massive MIMO operation with and without downlink training, for different network densities. We take also into account the performance improvement provided by max-min fairness power control in the downlink. Numerical results show that, exploiting downlink pilots, the performance can be considerably improved in low density networks over the conventional scheme where the users rely on statistical channel knowledge only. In high density networks, performance improvements are moderate., Funding Agencies|European Unions Horizon research and innovation programme [641985]

In this paper we consider a time-division duplex cell-free massive multiple-input multiple-output (MIMO) system where many distributed access points (APs) simultaneously serve many users. A normalized conjugate beamforming scheme, which satisfies short-term average power constraints at the APs, is proposed and analyzed taking into account the effect of imperfect channel information. We derive an approximate closed-form expression for the per-user achievable downlink rate of this scheme. We also provide, analytically and numerically, a performance comparison between the normalized conjugate beamforming and the conventional conjugate beamforming scheme in [1] (which satisfies long-term average power constraints). Normalized conjugate beamforming scheme reduces the beamforming uncertainty gain, which comes from the users lack of the channel state information knowledge, and hence, it improves the achievable downlink rate compared to the conventional conjugate beamforming scheme.

Target tracking with ultra-wideband (UWB) signals in indoor environments is a challenging problem due to the presence of multipath and non-line-of-sight conditions (NLOS). A solution to this problem is to use particle filtering (PF), which is able to handle both nonlinear models and non-Gaussian uncertainties that typically appear in the presence of NLOS. In this paper, we compare four different PF variants, that differ in terms of how NLOS measurements are handled. According to our experimental results, based on the measurements from a basement tunnel, multiple features from the UWB impulse response should be used, and the ranging likelihood function should make use of both LOS and NLOS measurements. Standard time-of-arrival (TOA) based methods, even with NLOS rejection, are not good enough. Instead we advocate TOA-based algorithms that can actively mitigate errors due to NLOS., COOPLOC

Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

In this paper we investigate a spectrum sensing technique suitable for cognitive radio (CR) considered a means to mitigate congestion in the future multiple access communication systems. The ultimate objective is opportunistic use of unoccupied frequency bands called spectrum holes or white spaces, which belong to another system. For this purpose, first, we identify the spectrum sensor (SS) nonlinearities and scan the available spectrum in wideband mode where the primary task is to identify strong interference. :Next, by a complementary analysis we pick up channels which are likely to be spectrum holes. In the second stage the SS is tuned to a selected sub-band by making use of a built-in flexible RF filter which largely attenuates interference and the related intermodulation distortions (IMD). The scan process carried out in this stage is aimed at detection of a vacant channel, i.e. containing only noise that must he distinguished from a possible weak signal that usually requires a significant computation overhead, but as the scan is narrowband and the S/N ratio can he high, the related overhead is largely reduced compared to the wideband sensing approach. The strength of this technique is in the flexible RF filter eliminating IMll which typically tend to obscure the spectrum holes.

Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

Target tracking with ultra-wideband (UWB) signals in indoor environments is a challenging problem due to the presence of multipath and non-line-of-sight conditions (NLOS). A solution to this problem is to use particle filtering (PF), which is able to handle both nonlinear models and non-Gaussian uncertainties that typically appear in the presence of NLOS. In this paper, we compare four different PF variants, that differ in terms of how NLOS measurements are handled. According to our experimental results, based on the measurements from a basement tunnel, multiple features from the UWB impulse response should be used, and the ranging likelihood function should make use of both LOS and NLOS measurements. Standard time-of-arrival (TOA) based methods, even with NLOS rejection, are not good enough. Instead we advocate TOA-based algorithms that can actively mitigate errors due to NLOS., COOPLOC

This paper considers the downlink of a heterogeneous network, where multiple base stations (BSs) can serve the users by non-coherent multiflow beamforming. We assume imperfect channel state information at both BSs and users. The objective is to jointly optimize the precoding, load balancing, and BS operation mode (active or sleep) for improving the energy efficiency of the network. The considered problem is to minimize the weighted total power consumption (both circuit power and dynamic transmit power), while satisfying per-user quality of service constraints and per-BS transmit power constraints. This problem is non-convex, but we prove that for each combination of BS modes, the considered problem has a hidden convexity structure. Thus, the global optimal solution is obtained by an exhaustive search over all possible BS mode combinations. Furthermore, by iterative convex approximations of the non-convex power consumption functions, a heuristic algorithm is proposed to obtain a local optimal solution with low complexity. Simulation results illustrate that our proposed algorithms significantly reduce the total power consumption, compared to the scheme where all BSs are continuously active. This implies that putting a BS into sleep mode by proper load balancing is an important solution for energy savings in heterogeneous networks.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a binoisy multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a binoisy multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a binoisy multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI) and M BS antennas. In particular, we consider two distinct operation modes, namely when the phase noise processes at the BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare the performance of the two modes. Based on the derived achievable sum-rate, we show that with the proposed receive processing an O() array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users., Manuscript received March 5, 2014; revised July 10, 2014; accepted September 6, 2014. Date of publication September 18, 2014; date of current version February 6, 2015. This work was supported in part by the Swedish Foundation for Strategic Research and in part by ELLIIT. The work of S. K. Mohammed was supported by the Science and Engineering Research Board, Department of Science and Technology, Government of India. This paper was presented in part at the 50th Allerton Conference on Communication, Control and Computing, Urbana-Champaign, IL, USA, October 2012. The associate editor coordinating the review of this paper and approving it for publication was L. Sanguinetti.

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI) and M BS antennas. In particular, we consider two distinct operation modes, namely when the phase noise processes at the BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare the performance of the two modes. Based on the derived achievable sum-rate, we show that with the proposed receive processing an O() array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users., Manuscript received March 5, 2014; revised July 10, 2014; accepted September 6, 2014. Date of publication September 18, 2014; date of current version February 6, 2015. This work was supported in part by the Swedish Foundation for Strategic Research and in part by ELLIIT. The work of S. K. Mohammed was supported by the Science and Engineering Research Board, Department of Science and Technology, Government of India. This paper was presented in part at the 50th Allerton Conference on Communication, Control and Computing, Urbana-Champaign, IL, USA, October 2012. The associate editor coordinating the review of this paper and approving it for publication was L. Sanguinetti.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a binoisy multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI) and M BS antennas. In particular, we consider two distinct operation modes, namely when the phase noise processes at the BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare the performance of the two modes. Based on the derived achievable sum-rate, we show that with the proposed receive processing an O() array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users., Manuscript received March 5, 2014; revised July 10, 2014; accepted September 6, 2014. Date of publication September 18, 2014; date of current version February 6, 2015. This work was supported in part by the Swedish Foundation for Strategic Research and in part by ELLIIT. The work of S. K. Mohammed was supported by the Science and Engineering Research Board, Department of Science and Technology, Government of India. This paper was presented in part at the 50th Allerton Conference on Communication, Control and Computing, Urbana-Champaign, IL, USA, October 2012. The associate editor coordinating the review of this paper and approving it for publication was L. Sanguinetti.

This paper introduces all-digital flexible channelizersand aggregators for multi-standard video distribution. The overall problem is to aggregate a number of narrow-band subsignals with different bandwidths (6, 7, or 8 MHz) into one composite wide-band signal. In the proposed scheme, this is carried out through a set of analysis filter banks (FBs), that channelize the subsignals into 1/2-MHz subbands, which subsequently are aggregated through one synthesis FB. In this way, full flexibility with a low computational complexity and maintained quality is enabled. The proposed solution offers orders-of-magnitude complexity reductions as compared with a straightforward alternative. Design examples are included that demonstrate the functionality, flexibility, and efficiency.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a binoisy multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI) and M BS antennas. In particular, we consider two distinct operation modes, namely when the phase noise processes at the BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare the performance of the two modes. Based on the derived achievable sum-rate, we show that with the proposed receive processing an O() array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users., Manuscript received March 5, 2014; revised July 10, 2014; accepted September 6, 2014. Date of publication September 18, 2014; date of current version February 6, 2015. This work was supported in part by the Swedish Foundation for Strategic Research and in part by ELLIIT. The work of S. K. Mohammed was supported by the Science and Engineering Research Board, Department of Science and Technology, Government of India. This paper was presented in part at the 50th Allerton Conference on Communication, Control and Computing, Urbana-Champaign, IL, USA, October 2012. The associate editor coordinating the review of this paper and approving it for publication was L. Sanguinetti.

For time division duplexing (TDD) systems, the physical channel in the air is reciprocal for uplink (UL) and downlink (DL) within the channel coherence time. However when the transceivers radio frequency (RF) hardware is taken into consideration, TDD channel reciprocity no longer holds because of the non-symmetric characteristics of RF transmit and receive chains. Relative calibration has been proposed to compensate this hardware impairment with a multiplicative matrix. In this paper we perform hardware measurements on this calibration matrix which gives a direct insight on the physical phenomenon of TDD transceivers. Especially, we inspect the assumption that this calibration matrix is diagonal, which is widely adopted in literature but has never been verified by experiments. This work can be regarded as an experimental base for TDD calibration or for theoretical analysis of non-perfect channel reciprocity of TDD systems.

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

The quality of RF N-path filtering is limited by the performance of the involved multiphase clock. The paper presents analysis of critical clock imperfections. The phase imbalance that gives rise to an extra image band located at second harmonic frequency is analyzed by a linear periodically varying (LPV) model of a 4-path filter where the respective rejection ratio is estimated and verified by simulation. We also analyze the clock phase noise and devise that the reciprocal mixing is not diminished by the attained blocker rejection, however, in this case one can benefit from band limitation by the output capacitance of the driving transconductance amplifier (LNTA). The analysis is supported by simulation results.

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI) and M BS antennas. In particular, we consider two distinct operation modes, namely when the phase noise processes at the BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare the performance of the two modes. Based on the derived achievable sum-rate, we show that with the proposed receive processing an O() array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users., Manuscript received March 5, 2014; revised July 10, 2014; accepted September 6, 2014. Date of publication September 18, 2014; date of current version February 6, 2015. This work was supported in part by the Swedish Foundation for Strategic Research and in part by ELLIIT. The work of S. K. Mohammed was supported by the Science and Engineering Research Board, Department of Science and Technology, Government of India. This paper was presented in part at the 50th Allerton Conference on Communication, Control and Computing, Urbana-Champaign, IL, USA, October 2012. The associate editor coordinating the review of this paper and approving it for publication was L. Sanguinetti.

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MINI is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

In this paper, we propose improved methods to select the most suitable frequency for transmission by also including information about the local interference environment. Knowledge of the local interference is included in the frequency selection through estimation of the interference power, and in addition through estimation of the impulsiveness of the interference. We evaluate the methods for both unicast and multicast scenarios using different performance measures, and show that the suggested methods can significantly reduce the bit error probability in relevant scenarios.

In this paper a technique suitable for on-chip IP3/IP2 RF test by embedded RF detectors is presented. A lack of spectral selectivity of the detectors and diverse nonlinearity of the circuit under test (CUT) impose stiff constraints on the respective test measurements for which focused calibration approach and a support by customized models of CUT is necessary. Also cancellation of second-order intermodulation effects produced by the detectors under the two-tone test is required. The test technique is introduced using a polynomial model of the CUT. Simulation example of a practical CMOS LNA under IP3/IP2 RF test with embedded RF detectors is presented showing a good measurement accuracy.

Far-field wireless recharging based on microwave power transfer (MPT) will free mobile devices from interruption due to finite battery lives. Integrating MPT with wireless communications to support simultaneous information-and-power transfer (SIPT) allows the same spectrum to be used for dual purposes without compromising the quality of service. In this paper, we propose the novel approach of realizing SIPT in a broadband downlink system where users are assigned orthogonal frequency sub-channels and a base station transfers information and energy to users over spatially separated channels called the data and MPT channels. Optimizing the power control for such a system results in a new class of multiuser power-control problems featuring the circuit-power constraints, namely that the wirelessly transferred power must be sufficiently large for operating receiver circuits. Solving these problems gives a set of power-control algorithms that exploit channel diversity in frequency for simultaneously enhancing the throughput and MPT efficiency. For the single-user SIPT system, the optimal power allocation is shown to perform water filling in frequency with water levels for different users depending on the corresponding MPT sub-channel gains. Next, an efficient power-control algorithm is proposed for the multiuser SIPT system based on sequential scheduling of mobiles by comparing their data rates and circuit-power constraints. This algorithm is proved to be optimal for the practical scenario of highly correlated data and MPT channels.

Target tracking in wireless sensor networks is traditionally achieved by localization and tracking (LAT), where the sensors are first localized, and in a later stage the target is tracked. This approach is sub-optimal since the sensor-target observations are not used to refine the position estimates of the sensors. In contrast, simultaneous localization and tracking (SLAT) uses these observations to track the target while simultaneously localizing the sensors. In this paper, we propose a novel centralized SLAT method based on real-time nonparametric belief propagation, which has nearly the same complexity and the same communication cost as LAT, and can provide both sensors' and target's estimated distributions in non-Gaussian form., COOPLOC

Large antenna arrays at the base station can facilitate power efficient single user downlink communication due to the inherent array power gain, i.e., under an average only total transmit power constraint, for a fixed desired information rate, the required total transmit power can be reduced by increasing the number of base station antennas (e. g. with i.i.d. fading, the required total transmit power can be reduced by roughly 3 dB with every doubling in the number of base station antennas, i.e., an O(N) array power gain can be achieved with N antennas). However, in practice, building power efficient large antenna arrays would require power efficient amplifiers/analog RF components. With current technology, highly linear power amplifiers generally have low power efficiency, and therefore linearity constraints on power amplifiers must be relaxed. Under such relaxed linearity constraints, the transmit signal that suffers the least distortion is a signal with constant envelope (CE). In this paper, we consider a single user Gaussian multiple-input single-output (MISO) downlink channel where the signal transmitted from each antenna is constrained to have a constant envelope (i.e., for every channel-use the amplitude of the signal transmitted from each antenna is constant, irrespective of the channel realization). We show that under such a per-antenna CE constraint, the complex noise-free received signal lies in the interior of a "doughnut" shaped region in the complex plane. The per-antenna CE constrained MISO channel is therefore equivalent to a doughnut channel, i.e., a single-input single-output (SISO) AWGN channel where the channel input is constrained to lie inside a "doughnut" shaped region. Using this equivalence, we analytically compute a closed-form expression for an achievable information rate under the per-antenna CE constraint. We then show that, for a broad class of fading channels (i.i.d. and direct-line-of-sight (DLOS)), even under the more stringent per-an

This paper considers multicell multiuser MIMO systems with verylarge antenna arrays at the base station. We propose an eigenvalue-decomposition-based approach to channel estimation, that estimates the channel blindly from the received data. The approach exploits the asymptotic orthogonality of the channel vectors in very large MIMO systems. We show that the channel to each user can be estimated from the covariance matrix of the received signals, up to a remaining scalar multiplicative ambiguity. A short training sequence is required to resolve this ambiguity. Furthermore, to improve the performance of our approach, we combine it with the iterative least-square with projection (ILSP) algorithm. Numerical results verify the effectiveness of our channel estimation approach.

Large antenna arrays at the base station can facilitate power efficient single user downlink communication due to the inherent array power gain, i.e., under an average only total transmit power constraint, for a fixed desired information rate, the required total transmit power can be reduced by increasing the number of base station antennas (e. g. with i.i.d. fading, the required total transmit power can be reduced by roughly 3 dB with every doubling in the number of base station antennas, i.e., an O(N) array power gain can be achieved with N antennas). However, in practice, building power efficient large antenna arrays would require power efficient amplifiers/analog RF components. With current technology, highly linear power amplifiers generally have low power efficiency, and therefore linearity constraints on power amplifiers must be relaxed. Under such relaxed linearity constraints, the transmit signal that suffers the least distortion is a signal with constant envelope (CE). In this paper, we consider a single user Gaussian multiple-input single-output (MISO) downlink channel where the signal transmitted from each antenna is constrained to have a constant envelope (i.e., for every channel-use the amplitude of the signal transmitted from each antenna is constant, irrespective of the channel realization). We show that under such a per-antenna CE constraint, the complex noise-free received signal lies in the interior of a "doughnut" shaped region in the complex plane. The per-antenna CE constrained MISO channel is therefore equivalent to a doughnut channel, i.e., a single-input single-output (SISO) AWGN channel where the channel input is constrained to lie inside a "doughnut" shaped region. Using this equivalence, we analytically compute a closed-form expression for an achievable information rate under the per-antenna CE constraint. We then show that, for a broad class of fading channels (i.i.d. and direct-line-of-sight (DLOS)), even under the more stringent per-an

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

In this paper, four transmit beamforming (BF) techniques are selected and compared to realize inter-operator spectrum sharing, which is a promising solution for the spectrum shortage problem. The BF techniques include two game-theoretic (GT) algorithms, zero-forcing (ZF) and minimum mean square error (MMSE). After a brief description of the BF techniques in a multiple-input single-output (MISO) system, their computational complexity is analyzed. The effectiveness of these techniques in real radio frequency (RF) signal transmission is verified by implementation on a flexible hardware-in-the-loop (HIL) testbed. First, several important aspects regarding practical implementation are discussed. Afterwards, the HIL measurement results are shown, where considerable sum rate gain can be observed due to spectrum sharing. Finally, the appropriate BF technique can be chosen based on a tradeoff between complexity and performance.