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Optimal Transmit Strategies for Multi-antenna Systems with Joint Sum and Per-antenna Power Constraints
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-0108-0749
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Nowadays, wireless communications have become an essential part of our daily life. During the last decade, both the number of users and their demands for wireless data have tremendously increased. Multi-antenna communication is a promising solution to meet this ever-growing traffic demands. In this dissertation, we study the optimal transmit strategies for multi-antenna systems with advanced power constraints, in particular joint sum and per-antenna power constraints. We focus on three different models including multi-antenna point-to-point channels, wiretap channels and massive multiple-input multiple-output (MIMO) setups. The solutions are provided either in closed-form or efficient iterative algorithms, which are ready to be implemented in practical systems.

The first part is concerned with the optimal transmit strategies for point-to-point multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) channels with joint sum and per-antenna power constraints. For the Gaussian MISO channels, a closed-form characterization of an optimal beamforming strategy is derived. It is shown that we can always find an optimal beamforming transmit strategy that allocates the maximal sum power with phases matched to the complex channel coefficients. An interesting property of the optimal power allocation is that whenever the optimal power allocation of the corresponding problem with sum power constraint only exceeds per-antenna power constraints, it is optimal to allocate maximal per-antenna power to those antennas to satisfy the per-antenna power constraints. The remaining power is distributed among the other antennas whose optimal allocation follows from a reduced joint sum and per-antenna power constraints problem with fewer channel coefficients and a reduced sum power constraint. For the Gaussian MIMO channels, it is shown that if an unconstraint optimal power allocation for an antenna exceeds a per-antenna power constraint, then the maximal power for this antenna is used in the constraint optimal transmit strategy. This observation is then used in an iterative algorithm to compute the optimal transmit strategy in closed-form.

In the second part of the thesis, we investigate the optimal transmit strategies for Gaussian MISO wiretap channels. Motivated by the fact that the non-secure capacity of the MISO wiretap channels is usually larger than the secrecy capacity, we study the optimal trade-off between those two rates with different power constraint settings, in particular, sum power constraint only, per-antenna power constraints only, and joint sum and per-antenna power constraints. To characterize the boundary of the optimal rate region, which describes the optimal trade-off between non-secure transmission and secrecy rates, related problems to find optimal transmit strategies that maximize the weighted rate sum with different power constraints are derived. Since these problems are not necessarily convex, equivalent problem formulation is used to derive optimal transmit strategies. A closed-formsolution is provided for sum power constraint only problem. Under per-antenna power constraints, necessary conditions to find the optimal power allocation are provided. Sufficient conditions, however, are available for the case of two transmit antennas only. For the special case of parallel channels, the optimal transmit strategies can deduced from an equivalent point-to-point channel problem. In this case, there is no trade-off between secrecy and non-secrecy rate, i.e., there is onlya transmit strategy that maximizes both rates.

Finally, the optimal transmit strategies for large-scale MISO and massive MIMO systems with sub-connected hybrid analog-digital beamforming architecture, RF chain and per-antenna power constraints are studied. The system is configured such that each RF chain serves a group of antennas. For the large-scale MISO system, necessary and sufficient conditions to design the optimal digital and analog precoders are provided. It is optimal that the phase at each antenna is matched tothe channel so that we have constructive alignment. Unfortunately, for the massive MIMO system, only necessary conditions are provided. The necessary conditions to design the digital precoder are established based on a generalized water-filling and joint sum and per-antenna optimal power allocation solution, while the analog precoder is based on a per-antenna power allocation solution only. Further, we provide the optimal power allocation for sub-connected setups based on two properties: (i) Each RF chain uses full power and (ii) if the optimal power allocation of the unconstraint problem violates a per-antenna power constraint then it is optimal to allocate the maximal power for that antenna. The results in the dissertation demonstrate that future wireless networks can achieved higher data rates with less power consumption. The designs of optimal transmit strategies provided in this dissertation are valuable for ongoing implementations in future wireless networks. The insights offered through the analysis and design of the optimal transmit strategies in the dissertation also provide the understanding of the optimal power allocation on practical multi-antenna systems.

Abstract [sv]

Trådlös kommunikation har idag kommit att bli en viktig del av våra dagliga liv. Under det senaste decenniet har både antalet användare och deras efterfrågan på trådlös data ökat enormt. Att utöka antalet antenner i sändare och mottagare är lovande strategier för att möta det ständigt ökande trafikbehovet. I den här avhandlingen studerar vi optimala transmissionsstrategier för multi-antennsystem med avancerade effektbegränsningar. Mer specifikt antas sammanlänkade begränsningar på total effekt och effekt per antenn. Vi fokuserar på tre olika modeller, nämligen multi-antenn punkt-till-punkt kanaler, wiretap-kanaler samt s.k. massiv MIMO (eng. multiple-input multiple-output) scenarier. Lösningar ges antingen i form av slutna matematiska uttryck, alternativt genom effektiva iterativa algoritmer redo att implementeras i praktiska system.

Den första delen av avhandlingen studerar optimala transmissionsstrategier för punkt-till-punkt MISO (eng. multiple-input single-output) samt MIMO-kanaler med sammanlänkade begränsningar på total effekt och effekt per antenn. För Gaussiska MISO-kanaler härleds en sluten karakterisering av en optimal ’beamforming’ -strategi. Vi visar att det alltid går att hitta en optimal ’beamforming’-strategi som allokerar den maximala totaleffekten med faser matchade till de komplexa kanalkoefficienterna. En intressant egenskap hos den optimala effektallokeringen är att närhelst den optimala effektallokeringen med enbart total effektbegränsning endast överskrider de individuella begränsningarna för specifika antenner, erhålls en optimal lösning genom att allokera maximal per-antenn effekt till just dessa antenner. Den återstående effekten distribueras sedan över de övriga antennerna enligt ett ekvivalent men reducerat optimeringsproblem med färre kanalkoefficienter. För Gaussiska MIMO-kanaler visas att om en obegränsad optimal effektallokering för en antenn överskrider den individuella, per antenn angivna, begränsningen så är maximal effekt allokerad för just dessa antenner i den optimala strategin. Denna observation används för att beskriva en iterativ algoritm som beräknar den optimala transmissionsstrategin.

I den andra delen av avhandlingen undersöker vi optimala transmissionsstrategier för Gaussiska MISO wiretap-kanaler. Motiverat av faktumet att den icke-säkrade kapaciteten över MISO wiretap-kanalen vanligtvis är större än den säkrade s.k. ’secrecy’-kapaciteten, studerar vi den optimala avvägningen mellan dessa två överföringshastigheter givet olika effektbegränsningar. Mer specifikt studeras total effektbegränsning enskilt, individuell effektbegränsning per antenn enskilt, samt sammanlänkade begränsningar på båda dessa. För att hitta regionsgränsen för optimala hastigheter, vilken beskriver den optimala avvägningen mellan icke-säkrad sändning och ’secrecy’-hastighet, härleds lösningar till relaterade problem där vi söker optimala transmissionsstrategier som maximerar den viktade summan av hastigheter med olika effektbegränsningar. Ekvivalenta formuleringar av optimeringsproblemen används för att härleda optimala transmissionsstrategier eftersom ursprungsproblemen ej är konvexa. En optimal lösning för problemet med total effektbegränsning ges i sluten form. För individuell effektbegränsning per antenn tillhandahåller vi nödvändiga villkor för att finna en optimal effektallokering. Tillräckliga villkor är endast tillgängliga i fallet av två sändarantenner. För specialfallet av parallella kanaler kan transmissionsstrategier härledas från ett ekvivalent problem för en punkt-till-punkt kanal. I detta fall existerar ingen avvägning mellan icke-säkrade och ’secrecy’ kapaciteten, endast en optimal strategi som maximerar båda kapaciteter.

Avslutningsvis studeras optimala strategier för storskaliga MISO samt massiva MIMO system med sammankopplad hybrid analog-digital ’beamforming’-arkitektur,  radiofrekvens-kedja samt individuella effektbegränsningar per antenn. Studerat system är konfigurerat så att varje radiofrekvens-kedja matar en grupp av antenner. För det storskaliga MISO systemet tillhandahålls nödvändiga och tillräckliga villkor för att design av optimala analoga och digitala kodningsstrategier ska vara möjligt. Optimal strategi uppnås då fasförskjutningen i varje antenn är matchad till motsvarande kanal, varvid konstruktiv samverkan uppstår. För massiv MIMO ges dessvärre endast nödvändiga villkor. De nödvändiga villkoren för att designa digitala kodningsstrategier etableras baserat på en generaliserad s.k. ’water-filling’ effektallokeringsmetod med sammanlänkade begränsningar på total effekt och effekt per antenn, medan villkoren för de analoga kodningsstrategierna endast är baserade på effektbegränsningar per antenn. Vidare beskriver vi optimal effektallokering för sammankopplade system baserat på två egenskaper: (i) Varje radiokedja utnyttjas till full effekt, samt (ii) i fallet då optimala effektallokeringen i det obegränsade problemet överskrider specifika antenners begränsningar fås den optimala lösningen genom att allokera maximal effekt till motsvarande antenner.Resultaten i denna avhandling visar att framtida trådlösa nätverk kan uppnå högre datahastigheter med lägre effektförbrukning. Den design av optimala transmissionsstrategier som beskrivs i denna avhandling är därför värdefulla i den pågående implementeringen av framtida trådlösa nätverk. De insikter som ges genom analys och design av optimala transmissionsstrategier i avhandlingen ger också förståelse inom optimal effektallokering i praktiska implementeringar av multi-antennsystem.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. , p. 26
Series
TRITA-EECS-AVL ; 2019:21
National Category
Engineering and Technology
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-247972ISBN: 978-91-7873-134-3 (print)OAI: oai:DiVA.org:kth-247972DiVA, id: diva2:1300866
Public defence
2019-04-26, Kollegiesalen, Brinellvagen 8, Stockholm, 13:30 (English)
Opponent
Supervisors
Available from: 2019-04-02 Created: 2019-03-29 Last updated: 2022-06-26Bibliographically approved
List of papers
1. Optimal Transmit Strategy for MISO Channels with Joint Sum and Per-antenna Power Constraints
Open this publication in new window or tab >>Optimal Transmit Strategy for MISO Channels with Joint Sum and Per-antenna Power Constraints
2016 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476Article in journal, Letter (Refereed) Published
Abstract [en]

In this paper, we study an optimal transmit strategy for multiple-input single-output (MISO) Gaussian channels with joint sum and per-antenna power constraints. We study in detail the interesting case where the sum of the per-antenna power constraints is larger than sum power constraint. A closed-form characterization of an optimal beamforming strategy is derived.It is shown that we can always find an optimal beamforming transmit strategy that allocates the maximal sum power with phases matched to the complex channel coefficients. The main result is a simple recursive algorithm to compute the optimal power allocation. Whenever the optimal power allocation of the corresponding problem with sum power constraint only exceeds per-antenna power constraints, it is optimal to allocate maximal per-antenna power to those antennas to satisfy the per-antenna power constraints. The remaining power is divided amongst the other antennas whose optimal allocation follows from a reduced joint sum and per-antenna power constraints problem of smaller channel coefficient dimension and reduced sum power constraint. Finally, the theoretical results are illustrated by numerical examples.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Sum power constraint, per-antenna power constraint, MISO, beamforming, transmit strategy, transmission rate.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-187650 (URN)10.1109/TSP.2016.2563382 (DOI)000380117400016 ()2-s2.0-84980395633 (Scopus ID)
External cooperation:
Note

QC 20160607

Available from: 2016-05-25 Created: 2016-05-25 Last updated: 2022-06-22Bibliographically approved
2. Optimal transmit strategy for MIMO channels with joint sum and per-antenna power constraints
Open this publication in new window or tab >>Optimal transmit strategy for MIMO channels with joint sum and per-antenna power constraints
2017 (English)In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2017, p. 3569-3573Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies optimal transmit strategies for multiple-input multiple-output (MIMO) Gaussian channels with joint sum and per-antenna power constraints. It is shown that if an unconstraint optimal allocation for an antenna exceeds a per-antenna power constraint, then the maximal power for this antenna is used in the constraint optimal transmit strategy. This observation is then used in an iterative algorithm to compute the optimal transmit strategy in closed-form. Finally, a numerical example is provided to illustrate the theoretical results.

Place, publisher, year, edition, pages
IEEE, 2017
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords
MIMO, sum power constraint, per-antenna power constraints, transmit strategy
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-209931 (URN)10.1109/ICASSP.2017.7952821 (DOI)000414286203146 ()2-s2.0-85023761054 (Scopus ID)978-1-5090-4117-6 (ISBN)
Conference
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 5-9 March 2017, New Orleans, LA, USA
Note

QC 20170627

Available from: 2017-06-26 Created: 2017-06-26 Last updated: 2024-03-18Bibliographically approved
3. Optimal Transmit Strategies for Gaussian MISO Wiretap Channels
Open this publication in new window or tab >>Optimal Transmit Strategies for Gaussian MISO Wiretap Channels
2018 (English)In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021Article in journal (Other academic) Submitted
Abstract [en]

This paper studies the optimal tradeoff between secrecy and non-secrecy rates of the MISO wiretap channels for different power constraint settings:sum power constraint only, per-antenna power constraints only and joint sum and per-antenna power constraints. The problem is motivated by the fact thatchannel capacity and secrecy capacity are generally achieved by different transmit strategies. First, a necessary and sufficient condition to ensure a positive secrecy capacity is shown. The optimal tradeoff between secrecy rate and transmission rate is characterized by a weighted rate sum maximization problem. Since this problem is not necessarily convex, equivalent problem formulations are introduced to derive the optimal transmit strategies. Under sum power constraint only, a closed-form solution is provided. Under per-antenna power constraints, necessary conditions to find the optimal power allocation are provided. Sufficient conditions are provided for the special case of two transmit antennas. For the special case of parallel channels, the optimal transmit strategies can deduced from an equivalent point-to-point channel problem. Lastly, the theoretical results are illustrated by numerical simulations.

National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-247970 (URN)
Note

QC 20190401

Available from: 2019-03-29 Created: 2019-03-29 Last updated: 2022-06-26Bibliographically approved
4. Transmit Beamforming for Single-User Large-Scale MISO Systems With Sub-Connected Architecture and Power Constraints
Open this publication in new window or tab >>Transmit Beamforming for Single-User Large-Scale MISO Systems With Sub-Connected Architecture and Power Constraints
2018 (English)In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 22, no 10, p. 2096-2099Article in journal (Refereed) Published
Abstract [en]

This letter considers optimal transmit beamforming for a sub-connected large-scale MISO system with RF chain and per-antenna power constraints. The system is configured such that each RF chain serves a group of antennas. For the hybrid scheme, necessary and sufficient conditions to design the optimal digital and analog precoders are provided. It is shown that, in the optimum, the optimal phase shift at each antenna has to match the channel coefficient and the phase of the digital precoder. In addition, an iterative algorithm is provided to find the optimal power allocation. We study the case where the power constraint on each RF chain is smaller than the sum of the corresponding per-antenna power constraints. Then, the optimal power is allocated based on two properties: each RF chain uses full power and if the optimal power allocation of the unconstraint problem violates a per-antenna power constraint then it is optimal to allocate the maximal power for that antenna.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Large-scale, massive MIMO, sub-connected architecture, hybrid beamforming, per-antenna power constraints
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-238138 (URN)10.1109/LCOMM.2018.2866265 (DOI)000447079300033 ()2-s2.0-85052681022 (Scopus ID)
Note

QC 20181108

Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2022-06-26Bibliographically approved
5. Precoding Design for Massive MIMO Systems with Sub-connected Architecture and Per-antenna Power Constraints
Open this publication in new window or tab >>Precoding Design for Massive MIMO Systems with Sub-connected Architecture and Per-antenna Power Constraints
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper provides the necessary conditions to design precoding matrices for massive MIMO systems with a sub-connected architecture, RF power constraints and per-antenna power constraints. The system is configured such that each RFchain serves a group of antennas. The necessary condition to design the digital precoder is established based on a generalized water-filling and joint sum and per-antenna optimal power allocation solution, while the analog precoder is based on a per-antenna power allocation solution only. We study the analytically most interesting case where the power constraint on the RF chain is smaller than the sum of the corresponding per-antenna power constraints. For this, the optimal power is allocated based on two properties: Each RF chain uses full power and if the optimal power allocation of the unconstraint problem violates a per-antenna power constraint then it is optimal to allocate the maximal power for that antenna.

Place, publisher, year, edition, pages
VDE Verlag GmbH, 2018
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-225420 (URN)2-s2.0-85069541670 (Scopus ID)
Conference
WSA 2018 - 22nd International ITG Workshop on Smart Antennas2018 22nd International ITG Workshop on Smart Antennas, WSA 2018, Bochum, 14-16 March 2018
Note

QCR 20180411

Available from: 2018-04-04 Created: 2018-04-04 Last updated: 2022-06-26Bibliographically approved

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