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Erik G. Larsson

Publications and source records attributed to Erik G. Larsson.

268 records · Page 15Linked to original sources

Massive MIMO for Next Generation Wireless Systems

Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned with roughly equal numbers of service-antennas and terminals and frequency division duplex operation, is not a scalable technology. Massive MIMO (also known as "Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension MIMO" & "ARGOS") makes a clean break with current practice through the use of a large excess of service-antennas over active terminals and time division duplex operation. Extra antennas help by focusing energy into ever-smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to intentional jamming. The anticipated throughput depend on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly-joined terminals, the exploitation of extra degrees of freedom provided by the excess of service-antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This paper presents an overview of the massive MIMO concept and contemporary research.

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Massive MU-MIMO Downlink TDD Systems with Linear Precoding and Downlink Pilots

We consider a massive MU-MIMO downlink time-division duplex system where a base station (BS) equipped with many antennas serves several single-antenna users in the same time-frequency resource. We assume that the BS uses linear precoding for the transmission. To reliably decode the signals transmitted from the BS, each user should have an estimate of its channel. In this work, we consider an efficient channel estimation scheme to acquire CSI at each user, called beamforming training scheme. With the beamforming training scheme, the BS precodes the pilot sequences and forwards to all users. Then, based on the received pilots, each user uses minimum mean-square error channel estimation to estimate the effective channel gains. The channel estimation overhead of this scheme does not depend on the number of BS antennas, and is only proportional to the number of users. We then derive a lower bound on the capacity for maximum-ratio transmission and zero-forcing precoding techniques which enables us to evaluate the spectral efficiency taking into account the spectral efficiency loss associated with the transmission of the downlink pilots. Comparing with previous work where each user uses only the statistical channel properties to decode the transmitted signals, we see that the proposed beamforming training scheme is preferable for moderate and low-mobility environments.

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Simultaneous Information and Power Transfer for Broadband Wireless Systems

Far-field microwave power transfer (MPT) will free wireless sensors and other mobile devices from the constraints imposed by finite battery capacities. 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. A novel approach is presented in this paper for realizing SIPT in a broadband system where orthogonal frequency division multiplexing and transmit beamforming are deployed to create a set of parallel sub-channels for SIPT, which simplifies resource allocation. Supported by a proposed reconfigurable mobile architecture, different system configurations are considered by combining single-user/multiuser systems, downlink/uplink information transfer, and variable/fixed coding rates. Optimizing the power control for these configurations results in a new class of multiuser power-control problems featuring circuit-power constraints, specifying that the transferred power must be sufficiently large to support the operation of the receiver circuitry. Solving these problems gives a set of power-control algorithms that exploit channel diversity in frequency for simultaneously enhancing the throughput and the MPT efficiency. For the system configurations with variable coding rates, the algorithms are variants of water-filling that account for the circuit-power constraints. The optimal algorithms for those configurations with fixed coding rates are shown to sequentially allocate mobiles their required power for decoding in the ascending order until the entire budgeted power is spent. The required power for a mobile is derived as simple functions of the minimum signal-to-noise ratio for correct decoding, the circuit power and sub-channel gains.

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Efficient Computation of Pareto Optimal Beamforming Vectors for the MISO Interference Channel with Successive Interference Cancellation

We study the two-user multiple-input single-output (MISO) Gaussian interference channel where the transmitters have perfect channel state information and employ single-stream beamforming. The receivers are capable of performing successive interference cancellation, so when the interfering signal is strong enough, it can be decoded, treating the desired signal as noise, and subtracted from the received signal, before the desired signal is decoded. We propose efficient methods to compute the Pareto-optimal rate points and corresponding beamforming vector pairs, by maximizing the rate of one link given the rate of the other link. We do so by splitting the original problem into four subproblems corresponding to the combinations of the receivers' decoding strategies - either decode the interference or treat it as additive noise. We utilize recently proposed parameterizations of the optimal beamforming vectors to equivalently reformulate each subproblem as a quasi-concave problem, which we solve very efficiently either analytically or via scalar numerical optimization. The computational complexity of the proposed methods is several orders-of-magnitude less than the complexity of the state-of-the-art methods. We use the proposed methods to illustrate the effect of the strength and spatial correlation of the channels on the shape of the rate region.

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Constant-Envelope Multi-User Precoding for Frequency-Selective Massive MIMO Systems

We consider downlink precoding in a frequency-selective multi-user Massive MIMO system with highly efficient but non-linear power amplifiers at the base station (BS). A low-complexity precoding algorithm is proposed, which generates constant-envelope (CE) signals at each BS antenna. To achieve a desired per-user information rate, the extra total transmit power required under the per-antenna CE constraint when compared to the commonly used less stringent total average transmit power constraint, is small.

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Achievable Outage Rate Regions for the MISO Interference Channel

We consider the slow-fading two-user multiple-input single-output (MISO) interference channel. We want to understand which rate points can be achieved, allowing a non-zero outage probability. We do so by defining four different outage rate regions. The definitions differ on whether the rates are declared in outage jointly or individually and whether the transmitters have instantaneous or statistical channel state information (CSI). The focus is on the instantaneous CSI case with individual outage, where we propose a stochastic mapping from the rate point and the channel realization to the beamforming vectors. A major contribution is that we prove that the stochastic component of this mapping is independent of the actual channel realization.

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Multi-Pair Amplify-and-Forward Relaying with Very Large Antenna Arrays

We consider a multi-pair relay channel where multiple sources simultaneously communicate with destinations using a relay. Each source or destination has only a single antenna, while the relay is equipped with a very large antenna array. We investigate the power efficiency of this system when maximum ratio combining/maximal ratio transmission (MRC/MRT) or zero-forcing (ZF) processing is used at the relay. Using a very large array, the transmit power of each source or relay (or both) can be made inversely proportional to the number of relay antennas while maintaining a given quality-of-service. At the same time, the achievable sum rate can be increased by a factor of the number of source-destination pairs. We show that when the number of antennas grows to infinity, the asymptotic achievable rates of MRC/MRT and ZF are the same if we scale the power at the sources. Depending on the large scale fading effect, MRC/MRT can outperform ZF or vice versa if we scale the power at the relay.

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PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink

We investigate an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme for large-scale multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. The use of OFDM causes a high peak-to-average (power) ratio (PAR), which necessitates expensive and power-inefficient radio-frequency (RF) components at the base station. In this paper, we present a novel downlink transmission scheme, which exploits the massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM modulation, and PAR reduction by solving a convex optimization problem. We develop a corresponding fast iterative truncation algorithm (FITRA) and show numerical results to demonstrate tremendous PAR-reduction capabilities. The significantly reduced linearity requirements eventually enable the use of low-cost RF components for the large-scale MU-MIMO-OFDM downlink.

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Uplink Performance Analysis of Multicell MU-MIMO Systems with ZF Receivers

We consider the uplink of a multicell multiuser multiple-input multiple-output system where the channel experiences both small and large-scale fading. The data detection is done by using the linear zero-forcing technique, assuming the base station (BS) has perfect channel state information. We derive new, exact closed-form expressions for the uplink rate, symbol error rate, and outage probability per user, as well as a lower bound on the achievable rate. This bound is very tight and becomes exact in the large-number-of-antennas limit. We further study the asymptotic system performance in the regimes of high signal-to-noise ratio (SNR), large number of antennas, and large number of users per cell. We show that at high SNRs, the system is interference-limited and hence, we cannot improve the system performance by increasing the transmit power of each user. Instead, by increasing the number of BS antennas, the effects of interference and noise can be reduced, thereby improving the system performance. We demonstrate that, with very large antenna arrays at the BS, the transmit power of each user can be made inversely proportional to the number of BS antennas while maintaining a desired quality-of-service. Numerical results are presented to verify our analysis.

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Per-antenna Constant Envelope Precoding for Large Multi-User MIMO Systems

We consider the multi-user MIMO broadcast channel with $M$ single-antenna users and $N$ transmit antennas under the constraint that each antenna emits signals having constant envelope (CE). The motivation for this is that CE signals facilitate the use of power-efficient RF power amplifiers. Analytical and numerical results show that, under certain mild conditions on the channel gains, for a fixed $M$, array gain is achievable even under the stringent per-antenna CE constraint (essentially, for a fixed $M$, at sufficiently large $N$ the total transmitted power can be reduced with increasing $N$ while maintaining a fixed information rate to each user). Simulations for the i.i.d. Rayleigh fading channel show that the total transmit power can be reduced linearly with increasing $N$ (i.e., an O(N) array gain). We also propose a precoding scheme which finds near-optimal CE signals to be transmitted, and has O(MN) complexity. Also, in terms of the total transmit power required to achieve a fixed desired information sum-rate, despite the stringent per-antenna CE constraint, the proposed CE precoding scheme performs close to the sum-capacity achieving scheme for an average-only total transmit power constrained channel.

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Single-User Beamforming in Large-Scale MISO Systems with Per-Antenna Constant-Envelope Constraints: The Doughnut Channel

Large antenna arrays at the base station (BS) has recently been shown to achieve remarkable intra-cell interference suppression at low complexity. However, building large arrays in practice, would require the use of power-efficient RF amplifiers, which generally have poor linearity characteristics and hence would require the use of input signals with a very small peak-to-average power ratio (PAPR). In this paper, we consider the single-user Multiple-Input Single-Output (MISO) downlink channel for the case where the BS antennas are constrained to transmit signals having constant envelope (CE). We show that, with per-antenna CE transmission the effective channel seen by the receiver is a SISO AWGN channel with its input constrained to lie in a doughnut-shaped region. For single-path direct-line-of-sight (DLOS) and general i.i.d. fading channels, analysis of the effective doughnut channel shows that under a per-antenna CE input constraint, i) compared to an average-only total transmit power constrained MISO channel, the extra total transmit power required to achieve a desired information rate is small and bounded, ii) with N base station antennas an O(N) array power gain is achievable, and iii) for a desired information rate, using power-efficient amplifiers with CE inputs would require significantly less total transmit power when compared to using highly linear (power-inefficient) amplifiers with high PAPR inputs.

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Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. Lower capacity bounds for maximum-ratio combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) detection are derived. A MRC receiver normally performs worse than ZF and MMSE. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option. The tradeoff between the energy efficiency (as measured in bits/J) and spectral efficiency (as measured in bits/channel use/terminal) is quantified. It is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single-antenna system.

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On Optimal Link Activation with Interference Cancellation in Wireless Networking

A fundamental aspect in performance engineering of wireless networks is optimizing the set of links that can be concurrently activated to meet given signal-to-interference-and-noise ratio (SINR) thresholds. The solution of this combinatorial problem is the key element in scheduling and cross-layer resource management. Previous works on link activation assume single-user decoding receivers, that treat interference in the same way as noise. In this paper, we assume multiuser decoding receivers, which can cancel strongly interfering signals. As a result, in contrast to classical spatial reuse, links being close to each other are more likely to be active simultaneously. Our goal here is to deliver a comprehensive theoretical and numerical study on optimal link activation under this novel setup, in order to provide insight into the gains from adopting interference cancellation. We therefore consider the optimal problem setting of successive interference cancellation (SIC), as well as the simpler, yet instructive, case of parallel interference cancellation (PIC). We prove that both problems are NP-hard and develop compact integer linear programming formulations that enable us to approach the global optimum solutions. We provide an extensive numerical performance evaluation, indicating that for low to medium SINR thresholds the improvement is quite substantial, especially with SIC, whereas for high SINR thresholds the improvement diminishes and both schemes perform equally well.

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Scaling up MIMO: Opportunities and Challenges with Very Large Arrays

This paper surveys recent advances in the area of very large MIMO systems. With very large MIMO, we think of systems that use antenna arrays with an order of magnitude more elements than in systems being built today, say a hundred antennas or more. Very large MIMO entails an unprecedented number of antennas simultaneously serving a much smaller number of terminals. The disparity in number emerges as a desirable operating condition and a practical one as well. The number of terminals that can be simultaneously served is limited, not by the number of antennas, but rather by our inability to acquire channel-state information for an unlimited number of terminals. Larger numbers of terminals can always be accommodated by combining very large MIMO technology with conventional time- and frequency-division multiplexing via OFDM. Very large MIMO arrays is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation. The ultimate vision of very large MIMO systems is that the antenna array would consist of small active antenna units, plugged into an (optical) fieldbus.

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Constant Envelope Precoding for Power-Efficient Downlink Wireless Communication in Multi-User MIMO Systems Using Large Antenna Arrays

We consider downlink cellular multi-user communication between a base station (BS) having N antennas and M single-antenna users, i.e., an N X M Gaussian Broadcast Channel (GBC). Under an average only total transmit power constraint (APC), large antenna arrays at the BS (having tens to a few hundred antennas) have been recently shown to achieve remarkable multi-user interference (MUI) suppression with simple precoding techniques. However, building large arrays in practice, would require cheap/power-efficient Radio-Frequency(RF) electronic components. The type of transmitted signal that facilitates the use of most power-efficient RF components is a constant envelope (CE) signal. Under certain mild channel conditions (including i.i.d. fading), we analytically show that, even under the stringent per-antenna CE transmission constraint (compared to APC), MUI suppression can still be achieved with large antenna arrays. Our analysis also reveals that, with a fixed M and increasing N, the total transmitted power can be reduced while maintaining a constant signal-to-interference-noise-ratio (SINR) level at each user. We also propose a novel low-complexity CE precoding scheme, using which, we confirm our analytical observations for the i.i.d. Rayleigh fading channel, through Monte-Carlo simulations. Simulation of the information sum-rate under the per-antenna CE constraint, shows that, for a fixed M and a fixed desired sum-rate, the required total transmit power decreases linearly with increasing N, i.e., an O(N) array power gain. Also, in terms of the total transmit power required to achieve a fixed desired information sum-rate, despite the stringent per-antenna CE constraint, the proposed CE precoding scheme performs close to the GBC sum-capacity (under APC) achieving scheme.

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Computational Complexity of Decoding Orthogonal Space-Time Block Codes

The computational complexity of optimum decoding for an orthogonal space-time block code G satisfying the orthogonality property that the Hermitian transpose of G multiplied by G is equal to a constant c times the sum of the squared symbols of the code times an identity matrix, where 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 [1],[2], 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.

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