We consider a MIMO communication system operating in dynamic time-division duplex, where one uplink (UL) access point (AP) detects information symbols transmitted from UL users (UEs) in the presence of AP-AP interference (AAI) caused by the signal a downlink (DL) AP transmits to a DL UE. We propose to mitigate the interference by jointly estimating the UL symbols and the AAI channel, but show that this problem is not uniquely solvable in the least-squares sense, and then present two methods for symbol detection that overcome this issue. Both methods let the UL UEs be silent in the first sample of each coherence interval. The first method performs joint symbol detection and AAI channel estimation for the remaining samples, while the second method does AAI channel estimation followed by interference subtraction. Despite the different nature of the two methods, we show that they are equivalent and that the variance of each symbol estimate is doubled compared to the genie case where the AAI is fully canceled. Numerical results verify our findings and show that our proposed methods offer a significant reduction in terms of the bit-error rate compared with the naive method where the AAI is not canceled.

We propose a decentralized subset method for optimal processing and combining of uplink signals in a distributed MIMO (D-MIMO) network. We further propose the use of Kalman filters with the square-root implementation to estimate the received uplink signals. This square-root implementation is shown to be numerically stable when inverting the covariance matrix, as it always assures the covariance matrix to be symmetric and positive semi-definite. In the paper we also analyze the computational complexity and cost with different combining methods. We show that the Kalman filter implementation provides the same result as the MMSE method in terms of the spectral efficiencies and equivalent SINR. However, the Kalman filter implementation is shown to be very efficient as it provides the possibility to fully utilize parallel computing of distributed hardware processors. Moreover, the processing can be decentralized and the estimates can be aggregated from local estimates to as many access points (APs) as needed to reach the desired performance target. A Kalman filter implementation has the flexibility to aggregate signals in different ways, allowing the fronthaul architecture to support connectivity of individual APs in any combination of parallel or serial manners.

We propose decentralized processing and combining in the uplink for a distributed MIMO (D-MIMO) network by a subset method. A subset that consists of a partial number of access points (APs) that are connected to a CPU is defined for each UE. A subset that consists of only one AP turns a D-MIMO network into "small cell" network; a subset that consists of all APs connected to the CPU give the same performance as a fully centralized method. The paper also shows that the subset method provides a very scalable trade-off between complexity and performance. It is simpler to realize as the processing can be distributed and parallelized. In the studied simulation scenarios, we show that it is possible to reach 85% of the performance upper bound by including only 20% of total APs in the subset, and to reach 95% of the performance upper bound by including 40% of APs in the subset.

A method for massive MIMO antenna muting for reducing energy consumption in 5G NR is presented and system level evaluated results is provided. By utilizing both polarizations of a dual-polarized antenna array the resulting beam shape can be kept constant as the number of active antenna elements are changed. This enables the number of active antenna elements in a large-scale antenna array to be adapted to traffic variations without affecting the system coverage. Hence the energy consumption associated with having a large antenna array can be avoided whenever the additional performance is not required. The results indicate that massive MIMO antenna muting can reduce the base station energy consumption with up to 30% without significantly degrading the system performance and user throughput. Results for dynamically down scaling of massive MIMO array sizes from 128 single polarized antenna elements to 64, 32 and 16 active antenna element configurations are presented.

The new 3GPP New Radio standard (NR) has been designed with deployment flexibility in mind to enable high-rate mobile broadband services as well as massive and ultra-low latency machine type communications for verticals. In this paper, we discuss the challenges and potential solutions to provide full surface coverage based on main-stream terrestrial cellular 3GPP technology to enable all use-cases. New 3GPP based solutions for improving coverage e.g. using 5G for self-backhauling, resource sharing, and protocol parameters are discussed. The paper includes results on the impact of selected link-budget improvements on cellular coverage under given capacity assumptions. It is shown that long-range systems with enough capacity are feasible with inter-site distances of 65 km with 5G on mid-band (3.5 GHz) notably reducing total cost of ownership.

In this paper we study the impact on radio network energy consumption, system capacity and end-user performance when deploying 5G NR street-macro cells in a dense urban area. The network energy consumption is a significant part of the operator OPEX [1], and here NR has a clear advantage over LTE thanks to the lean design of the physical layer enabling more efficient hardware sleep during times with low traffic [2]. To evaluate the energy performance advantage of 5G NR we perform system evaluations in a scenario based on a real network in a European capital city. First, we study a NR-only scenario where high-power NR "street-macro cells" are added to a network of above-rooftop NR macro cells. Secondly, we examine a network migration scenario where NR is added to an existing LTE deployment and we show that in a dense urban scenario with very high traffic the network energy consumption is decreased by introducing NR. In both scenarios the street-macro cells increase the total system capacity as well as the cell-edge user throughput performance significantly. When cell sleep functionality utilizing discontinuous transmission (DTX) is used these performance enhancements are achieved without increasing the total network energy consumption.

Ubiquitous cell-free massive MIMO (multiple-input multiple-output) combines massive MIMO technology and user-centric transmission in a distributed architecture. All the access points (APs) in the network cooperate to jointly and coherently serve a smaller number of users in the same time-frequency resource. However, this coordination needs significant amounts of control signalling which introduces additional overhead, while data co-processing increases the back/front-haul requirements. Hence, the notion that the “whole world” could constitute one network, and that all APs would act as a single base station, is not scalable. In this study, we address some system scalability aspects of cell-free massive MIMO that have been neglected in literature until now. In particular, we propose and evaluate a solution related to data processing, network topology and power control. Results indicate that our proposed framework achieves full scalability at the cost of a modest performance loss compared to the canonical form of cell-free massive MIMO.

In this paper we compare the energy consumption of the 3GPP standards 5G New Radio (NR) and Long-Term Evolution (LTE). We show that the energy consumption in an idle network (without user plane traffic) can be up to 9 times lower for an NR stand-alone network compared to an LTE network. The network energy consumption in low or no traffic scenarios is a significant part of the operator OPEX in low traffic areas [1], such as in extreme rural scenarios, and here NR has a clear advantage compared to LTE. To evaluate the energy performance advantage of NR when we have very high traffic, such as in Super-Dense Urban and Urban scenarios, we perform system evaluations. We show that if we increase capacity in an existing LTE network with additional NR micro cells compared to using additional LTE cells, the reduction in network energy consumption is close to 50 percent. If we also upgrade the LTE cells in the macro coverage layer to NR a total energy reduction of up to 70 percent is achievable.

The new 3GPP New Radio standard (NR) has the potential of providing high rate mobile broadband services for very long range (resulting in very low cost per subscriber) utilizing the 3.5 GHz band. In this paper, we discuss the techno- economic problems associated with providing high quality mobile broadband services to under-served areas and propose best practice enhancements for the network as well as for the terminals. On the terminal side, a solution based on low-cost user deployed booster equipment combined with access to local spectrum for rural hot-spots is proposed. On the network side we utilize high gain massive MIMO antennas. To reach the large fraction of the world’s population that are under GSM coverage, these are deployed on existing GSM sites. As a complement, they can also be deployed on high TV- towers. We also briefly discuss spectrum and policy aspects, which have a very large impact on the rural cellular market. We show that on an existing GSM-grid planned for voice coverage, it is possible to reach downlink data rates exceeding 100 Mbps at cell edge with 5G NR using conventional terminals and normal base station equipment, however the uplink performance is not adequate in this scenario. By enhancing the network and terminal hardware we can reach more than 350 Mbps in the DL and more than 30 Mbps in the UL. Additionally, using taller base station towers we can extend the coverage far beyond that enabled by typical GSM sites.

In this paper we evaluate the performance impact of introducing the new deep sleep state features that may be deployed in 5G NR base stations. We evaluate the effects on traffic performance and energy efficiency by applying an updated power consumption model. Previously proposed power models may be too optimistic and thus the impact of a new more conservative power model has been investigated. A sensitivity analysis is also performed to understand the effects on the KPIs with various parameter settings of the power model. In the evaluations we show that the energy savings that is achievable by using a more conservative power model is still very high and that the impact on user performance can be small if the sleep states are applied in a thoughtful manner. Up to 80% energy savings is possible to achieve in a 5G hetnet scenario. The performance impact can be limited to a few percent extra delay on file transmissions. It is also found that even quite large modifications to the power model give similar results.

Cell-free Massive MIMO (multiple-input multiple-output) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works demonstrated that, unlike co-located Massive MIMO, the channel hardening is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the previously proposed analysis to non-orthogonal uplink and downlink pilots. Assuming single-antenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the per-user achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacity-bounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.

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.

In this paper, we revisit the radio network energy performance evaluation methodology, commonly known as E3F, that was developed in the European EARTH project during 2010-2011. We propose updates to the large-scale deployment and long-term traffic models in order to reflect the situation in a 5G time frame, and also an improvement in the sense that the baseline network is dimensioned to exactly meet the traffic and performance requirements. As an example, we apply the methodology in order to dimension and evaluate the energy performance of a state-of-the-art country-wide LTE network. The inter site distances of the resulting network range from 380 m in super dense urban (serving 20,000 citizens/km2) to 4850 m in rural areas (serving 100 citizens/km2). The resulting average power per area unit is 0.14 kW/km2, which is significantly lower than what was found in the EARTH project. This can be explained by two factors: i) The present study assumes more efficient base stations, and ii) the baseline network of the original E3F was over-dimensioned. Nevertheless, the conclusion from the EARTH project, that the absolute majority of energy consumed in a radio network is spent on providing coverage, still remains.

In this paper, we evaluate the technology potential of a new 5G radio access technology (RAT), here denoted 5G-NX, in terms of energy performance at the country level, in order to show what can be expected in the future when networks are being modernized and new technology is rolled out. To this end, per deployment area we calculate the daily energy consumption via system level simulations considering a typical European country categorized by six deployment areas, and extend the results to country scale according to a large-scale deployment model. The results show that 55% energy saving is achievable at the country level with 5G-NX networks while providing up to 15 times more capacity and 9 times higher peak rate compared to a baseline LTE network using the same site grid.

This paper presents the energy performance of a new radio access technology (RAT) component in 5G, here denoted as 5G-NX. The 5G-NX RAT encompasses massive beamforming and an ultra-lean design as two of its key technology components. The user throughput, resource utilization of the cells and daily average area power consumption are evaluated by means of system level simulations in an Asian city scenario, and the results are compared with a traditional LTE deployment using the same network layout. The simulation results indicate that the new 5G-NX system provides much better energy performance compared to LTE and this is primarily due to the ultra-lean design and the high beamforming gain that provides both longer and more efficient component sleep in the network. At expected traffic levels beyond 2020, 5G-NX is shown to decrease the network energy consumption by more than 50% while providing around 10 times more capacity.

In this paper we examine the energy and user performance that can be achieved by combining antenna muting and dynamic three-sector to psi- omni site reconfiguration. A detailed algorithm is proposed for how to change on a sub-second timescale between a MIMO capable sector covering mode optimized for capacity, to a single transmit antenna psi-omni covering mode optimized for low energy consumption. Performance evaluations, in accordance with the EARTH energy efficiency evaluation framework (E3F), show that in a nationwide LTE network the largest energy savings with the proposed algorithm are found in rural environments. By applying dynamic antenna muting we achieve 24.9% energy savings compared to the reference case without antenna muting. And by combining dynamic psi-omni coverage together with antenna muting energy savings of 43.8% were achieved. In the evaluations of the latter case we experienced a drop in average user bitrate of 10.7% when both algorithms (antenna muting and dynamic sector-omni reconfiguration) were applied. This performance drop is likely to be somewhat over-estimated.

This paper evaluates the technology potential of using massive MIMO beamforming as a tool to enhance energy performance of radio networks. The geometry, user bit rate, required inter site distance, area power, discontinuous transmission ratio, and relative power consumption during transmission is evaluated by means of system level simulations and the results are compared with a traditional three-sectorized deployment. The simulation results indicate that massive MIMO beamforming can reduce network area power consumption significantly; especially if the gains are taken into account in the network planning process by enabling a deployment with larger inter site distance compared to the reference three-sectorized deployment without massive MIMO antenna systems. As an example we note that 5 dB additional link budget achieved by the massive MIMO beamforming can be used to reduce network area power consumption with 50% if we design the network for a 10 Mbps cell edge user throughput target.

This paper presents a clean slate radio network solution, that has been designed with the aim to maximize energy performance. In traditional radio network designs, the energy cost for providing coverage (idle mode functionality) is totally dominating the network energy consumption. Here, a logical separation between idle mode functions and user plane data transmission and reception will be assumed. This allows us to meet the key challenge of reducing idle mode energy consumption in the network by designing for DTX and DRX also in the network nodes. The clean slate energy optimized system design targets this challenge with a new way of transmitting system information and performing initial system access. To illustrate the technology potential of the solution a simple system level evaluation is provided. It is shown that the gain of transmitting system information in a single frequency network (SFN) format is shown to be more than 4 dB at an inter site distance (ISD) of 10000 meters. Furthermore, with certain assumptions on future hardware it is estimated that the proposed concept can reduce area power consumption with up to 95% compared to a reference system of today.

Dynamic base station downlink discontinuous transmission (DTX) operations have been proposed and under discussion in the standardization body as a candidate to reduce interference in the LTE network to support rapidly increasing demand for mobile broadband services and traffic volumes [1]. In this paper, we analyze the energy efficiency improvement of the dynamic base station DTX operations from three perspectives. First, we discuss the complementary operation aspect of the dynamic base station DTX and existing LTE dormant mode. Secondly, we provide an analysis showing substantial energy efficiency benefits at all loads of dynamic base station DTX operation with near- future base station hardware components. Thirdly, we provide an analytical framework to assess the energy saving potential of the dynamic base station DTX concept for all possible future hardware improvement possibilities.

Modern radio base stations (RBSs) typically consist of components such as radio units (RUs) and digital units (DUs) that are capable of supporting multiple radio access technologies (RATs) at the same time. This enables several different possible configurations of a multi-RAT site and in this paper we assess the energy performance of some promising configurations. We start by evaluating an LTE-only network and conclude that with traffic according to predictions for 2015 the average cell will be idle 95% of the time and the additional energy consumption due to the user plane traffic is only 1.4%. We also show that even a significant future traffic increase will only have a minor impact on the energy consumption. We further show in this paper that a multi-RAT RBS where the RATs share the digital unit (PA) have the potential to reduce the site energy consumption with 40% compared to a multi-RAT RBS with separate PAs for each RAT. For operators with multiple RATs on the same site but using separate PAs per RAT, it is still possible to reduce energy consumption by utilizing load balancing between the RATs. This study shows that a potential energy reduction in the order of 30% is possible by utilizing load balancing between HS and LTE.

In 2020, mobile access networks will experience significant challenges as compared to the situation of today. Traffic volumes are expected to increase 1000 times, and the number of connected devices will be 10-100 times higher than today in a networked society with unconstrained access to information and sharing of data available anywhere and anytime to anyone and anything. One of the big challenges is to provide this 1000-fold capacity increase to billions of devices in an affordable and sustainable way. Low energy consumption is the key to achieve this. This paper takes as starting point the situation of today, and tries to pinpoint important focus areas and potential solutions when designing an energy efficient 5G mobile network architecture. These include system architecture, where a logical separation of data and control planes is seen as a promising solution; network deployment, where (heterogeneous) ultra dense layouts will have a positive effect; radio transmission, where the introduction of massive antenna configurations is identified as an important enabler; and, finally, backhauling solutions that need to be more energy efficient than today.

Link level performance results for physical antenna port muting in LTE are presented. In this paper we examine the block error rate performance of the LTE downlink control channels (PBCH, PCFICH, PDCCH, and the PHICH) for different antenna muting configurations. Also the throughput performance of the LTE downlink data channel (PDSCH) is studied for 2Tx and 4Tx transmit diversity formats. The results show that the combination of logical antenna port merging with physical antenna port muting provides a very minor performance loss. Since antenna muting should only be used when the traffic in a cell is low, this performance loss is not significant in practice. With antenna muting we can save energy by activating radio units only when motivated by the traffic load in the cell.

The concept of antenna muting for reducing energy consumption in LTE is presented and system level evaluation results are provided. The results indicate that antenna muting can reduce the energy consumption with up to around 50% in a low load scenario without significantly affecting the user throughput. Results for 4TX, 2TX, and 1TX cell configurations are presented. The system level simulator used includes detailed models of UE pre-coder selection and feedback and we show in this paper that these algorithms performs well also when antennas are muted in a way that was not considered during the design of the algorithms. Antenna muting is a promising technique that operates on a rather short time scale in order to reduce the energy consumption of an LTE cell.

Energy consumption in mobile networks, e.g. 3G networks, may be a substantial part of an operator''s expenses. A large part of the total energy of the network is consumed by the radio access network. One promising way to reduce the energy consumption of the radio network is to deactivate radio units during periods with low load. Significant gains can be achieved using this approach since each radio unit, connected to an antenna, has relatively high energy consumption during idle periods. In this paper we evaluate an approach where the number of active radio units needed for handling the traffic is computed based on the traffic load. This approach is evaluated using traffic measurements from a 3G network in a European city during 2009 and the results show that an energy saving around 50% is achievable. This suggests that there is potential for significantly enhancing energy efficiency in mobile networks by adaptive activation of radio units.

Control signaling strategies for scheduling information in cellular OFDM systems are studied. A single-cell multiuser system model is formulated that provides system capacity estimates accounting for the signaling overhead. Different scheduling granularities are considered, including the one used in the specifications for the 3G Long Term Evolution (LTE). A greedy scheduling method is assumed, where each resource is assigned to the user for which it can support the highest number of bits. The simulation results indicate that the cost of control signaling does not outweigh the scheduling gain, when compared with a simple round-robin scheme that does not need signaling of scheduling information. Furthermore, in the studied scenario, joint coding and signaling of scheduling information over all selected users is found to be superior to separate coding and signaling for each user. The results also indicate that the scheduling granularity used for LTE provides better performance than the full granularity.

Radio network management simplification concerns to some extent the removal, not the simplification, of tasks. In this paper we present an approach for automatic network management in 3G long term evolution (LTE), namely, methods for automatic configuration of locally-unique physical cell identities and neighbor cell relation lists. We show that these issues can be removed from the list of planning tasks and completely replaced by autonomous algorithms. These algorithms make use of mobile measurements to detect local cell identity conflicts, resolve them, and to update the neighbor cell relation lists in the cells. The performance of the approach is determined using simulations of realistically deployed macro networks. The simulations illustrate the ability of the algorithms to resolve local cell identity conflicts. In particular, the algorithms are capable of both accommodating new cells and handling a worst case scenario where all cells are initiated with the same local cell identities and where neighbor cell relation lists are empty. The contributions in this paper are meant to aid operators by allowing them to replace time consuming and costly tasks with automatic mechanisms, thus, reducing operational expenditure.

This paper discusses the requirements on future radio access and, based on the requirements, proposes a framework for such a system. The proposed system based on orthogonal frequency-division multiplexing supports very low latencies and data rates up to 100 Mb/s with wide area coverage and 1 Gb/s with local area coverage. Spectrum flexibility is identified as one main requirement for future systems, and the proposed framework can be deployed in a wide range of spectrum allocations with bandwidths ranging from 2.5 to 100 MHz. Multihop relaying, useful to extend the range for the high data rates, and multiple-antenna configurations are integral parts of the framework. A packet-centric approach is taken for the dataflow processing, implying that the scheduling mechanism and the retransmission protocol operate on complete packets rather than segments thereof, thus allowing for cross-layer optimization. Finally, numerical evaluations are provided, illustrating the feasibility of future very wideband radio access.

The first step of evolving WCDMA towards higher data rates through the introduction of HSDPA is discussed. By applying fast link adaptation together with higher order modulation, fast hybrid ARQ and fast scheduling, the best-effort packet data support of WCDMA can be improved in terms of increased throughput, lower delays and increased peak data rates. Simulations illustrate the potential of the concept.

Discrete multitone modulation allows for a simple receiver structure if the impulse response of the communication channel is shorter than the cyclic prefix. In ADSL, a time-domain equalizer (TEQ) is used to fulfil this requirement. Without a TEQ, unwanted intercarrier interference (ICI) and intersymbol interference (ISI) occur. In this paper, quadratic forms are developed to calculate the contributions of ICI and ISI to the desired signal. Based on these expressions, a new method for calculating the TEQ coefficients, which minimizes the effects of ICI, ISI, and additive noise, is derived. Simulations in the context of ADSL compare the performance of this new algorithm with one that is state of the art.

We compare two hybrid automatic repeat request (HARQ) combining strategies that currently are considered for the high speed downlink packet access (HSDPA) evolution of WCDMA. The two HARQ combining schemes are Chase combining, where the retransmissions are identical copies of the original transmission, and incremental redundancy (IR), where the retransmissions consist of new parity bits from the channel encoder. We show that the link-level performance of a HARQ type-II system can be significantly better with IR compared to Chase combining. The largest gains are obtained for high channel-coding rates and high modulation orders. For low modulation and coding schemes (MCS), the link-level performance gains with IR are less significant. We further show that in a system that uses link adaptation we can not expect any large gains with IR as long as the link adaptation errors are reasonably small. Furthermore, we show that on fading channels there are situations when an IR system actually performs poorer than a Chase combining system.

Recent publications on new improved convolutional codes claim different codes to be optimum under the optimum distance spectrum (ODS) criterion. This correspondence presents results from a study independent of the previous works, and seeks to clarify some inconsistencies. In addition, some new improved feed-forward convolutional encoders are presented.

A new metric for turbo decoding on Rayleigh fading channels with noisy channel estimates is derived. By including the error variance of the channel estimate in the decoder metric derivation, we calculate the correct channel reliability factor for this case. Simulations show that the signal-to-noise ratio gain of using this new metric, compared to ignoring the uncertainty of the channel estimate, may be as large as 1 dB at a bit error probability of 10/sup -3/. This gain is obtained without any complexity increase.

In code division multiple-access (CDMA) systems, maximum total throughput assuming a matched filter receiver can be obtained by spreading with low-rate error control codes. Previously, orthogonal, bi-orthogonal and super-orthogonal codes have been proposed for this purpose. We present in this paper a family of rate-compatible low-rate convolutional codes with maximum free distance. The performance of these codes for spectrum spreading in a CDMA system is evaluated and shown to outperform that of orthogonal and super-orthogonal codes as well as conventionally coded and spread systems. We also show that the proposed low rate codes will give simple encoder and decoder implementations. With these codes, any rate 1/n, n/spl les/512, are obtained for constraint lengths up to 11, resulting in a more flexible and powerful scheme than those previously proposed.

New rate-compatible convolutional (RCC) codes with high constraint lengths and a wide range of code rates are presented. These new codes originate from rate 1/4 optimum distance spectrum (ODS) convolutional parent encoders with constraint lengths 7-10. Low rate encoders (rates 115 down to 1/10) are found by a nested search, and high rate encoders (rates above 1/4) are found by rate-compatible puncturing. The new codes form rate-compatible code families more powerful and flexible than those previously presented. It is shown that these codes are almost as good as the existing optimum convolutional codes of the same fates. The effects of varying the design parameters of the rate-compatible punctured convolutional (RCPC) codes, i.e., the parent encoder rate, the puncturing period, and the constraint length, are also examined. The new codes are then applied to a multicode direct-sequence code-division multiple-access (DS-CDMA) system and are shown to provide good performance and rate-matching capabilities. The results, which are evaluated in terms of the efficiency for Gaussian and Rayleigh fading channels, show that the system efficiency increases with decreasing code rate.