Chapter 6: Intercell Interference Coordination: Towards A Greener Cellular Network

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Chapter 6Intercell Interference Coordination
Towards A Greener Cellular Network
HANDBOOK ON GREEN INFORMATION AND COMMUNICATION
SYSTEMS

• Duy T. Ngo, Duy H. N. Nguyen, and Tho Le-Ngoc
• McGill University
• Montreal, QC, Canada

2
Introduction

• Intercell interference (ICI) is a critical issue
  in cellular communication systems.
• With universal frequency reuse, it is even more
  urgent to find effective solutions to this
  problem.
• Energy efficiency is crucial
• Environmental effects of operating a huge number
  of cellular networks with high energy consumption
  
• Battery-powered user terminals have relatively
  short operating time
• Towards a greener design, effective coordination
  of the intercell interference is key to
• Minimize the carbon footprint
• Maximize the overall network performance

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Introduction

• Cell coordination offers tremendous advantages
  over the traditional approaches that typically
  treat interference on a per-cell basis.
• This chapter reviews the state-of-the-art
  techniques that manage the intercell interference
  in multicell networks
• Homogeneous networks
• Coordinated multipoint transmission and reception
  (CoMP)
• Small-cell heterogeneous networks (femtocells)
• Energy-efficient interference coordination

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Frequency Reuse and Interference Issue in
Homogeneous Cellular Systems

• Broadcast nature of wireless medium results in
  the fundamental problem of interference.
• Fractional frequency reuse
• Reduced spectral efficiency
• Universal frequency reuse
• More spectrally efficient
• Only if intercell interference (ICI) is properly
  control.
• CDMA systems
• All users (UEs) share the same spectrum and are
  interfered.
• OFDMA systems
• Joint subchannel assignment and power control is
  required to maximize system performance and
  reduce ICI.

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BS Coordination for Interference Management in
Homogeneous Multicell Systems

• Conventionally, interference is usually
  controlled on a per-cell basis.
• The ICI is treated as background noise by each
  cell, and the base station (BS) of which has no
  intention to control the interference induced to
  other cells.
• Base station (BS) coordination is a more
  effective means to mitigate cochannel
  interference in multicell networks.
• Coordinated multipoint transmission and reception
  (CoMP) takes advantage of the inter-cell
  transmissions to enhance the overall system
  performance.

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Classification and Design Requirements for CoMP

• Depending on the extent of coordination among
  cells, CoMP schemes can be classified into 3
  categories
• Joint Signal Processing (JP) multiple BSs are
  transmitting/receiving data signals to/from the
  UEs.
• Interference Coordination (IC) each UE
  transmits/receives data signals to/from its
  single serving BS. ICI is jointly controlled.
• Interference Aware (IA) ICI is not controlled,
  but is utilized to adjust the transmitting/receivi
  ng strategy at each BS. This scheme is a
  strategic noncooperative game (SNG).
• Different CoMP schemes impose different
  requirements on
• Data and signaling exchanges.
• Channel state information (CSI) knowledge needed
  at the coordinated BSs.

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Co-channel Deployment of Heterogeneous
Small-cell Networks

• Key Benefits
• Higher capacity via larger area spectral
  efficiency
• Better coverage with lower power consumption
• Offload traffic for macrocell
• More cost-effective compared to cell-partitioning
  approach

• Small cells (i.e. femtocells) deployed at a home,
  connected to backhaul via residential wireline
  links (e.g. DSL).
• Range of less than 50m and serve a dozen active
  users

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Cross-tier Interference in Femtocell Deployment

• Scenario A
• A victim cell-edge macrocell user (MUE) is
  strongly interfered by the downlink transmission
  of a nearby femtocell BS.
• Scenario B
• An MUE located far away from its serving
  macrocell BS transmits at high power in the
  uplink to compensate the path losses.
• This may jam the transmission of a nearby victim
  femtocell user (FUE).

• Cross-tier interference can be severe and hard
  to control

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Challenges in Managing Interference for Femtocell
Networks

• It is more challenging to mitigate inteference in
  femtocell than in traditional homogeneous
  settings.
• Unplanned deployment Femtocells are deployed
  randomly without network planning that is
  normally taken place. Femtocell BSs and users can
  be moved or switched on/off at any time.
• Access priority Prioritized MUEs, the spectrum
  owner, need to be protected from cross-tier
  interference induced by lower-tier FUEs.
• Limited control/signaling Residential network
  infrastructure only provide limited capacity for
  the exchange of control and signaling
  information. Delay can be a major issue.

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Interference Management in Femtocell Networks
Design Requirements

• Femtocell deployment A paradigm shift from the
  traditional centralized macrocell approaches to a
  more uncoordinated and autonomous solution
• Available centralized solutions may not be
  applicable.
• Distributed interference management approaches
  are preferable in practical applications so that
• MUEs are robustly protected with their QoS
  requirements always maintained and
• FUEs effectively exploit residual network
  capacity to optimize their own performance.

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Interference Management Techniques in CDMA-based
Homogeneous Cellular Networks (1)

• Power control is effective for CDMA-based systems
• SINR/Power balancing can be implemented
  distributively, but diverges with infeasible SINR
  targets
• Game-theoretical approach users selfishly
  optimize their own performance, giving Nash
  equilibrium (NE), but not Pareto-efficient.
• Game with pricing can substantially enhance the
  NE.

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Interference Management Techniques in CDMA-based
Homogeneous Cellular Networks (2)

• Using pricing scheme that is linearly
  proportional to SINR, i.e., , NE is unique and
  Pareto-efficient for single-cell settings.
• Observe SINRs should not be fixed but adjusted
  to the extent that the system capacity can still
  support.
• A high SINR is translated into better throughput
  and reliability
• A low SINR implies lower data rates.
• Jointly optimize SINR and power to achieve Pareto
  optimality by
• Re-parametrization via the left Perron-Frobenius
  eigenvectors
• A locally computable ascent direction

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Interference Management Techniques in OFDMA-based
Homogeneous Cellular Networks (1)

• Optimize over 2 dimensions
• Joint subchannel assignment and power allocation
• Typical design problem
• Common approach
• Step 1 Given fixed power allocation P, find
  optimal subchannel assignment i
• Step 2 Given fixed subchannel assignment i, find
  optimal power P
• Go back to Step 1 and repeat until convergence.

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Interference Management Techniques in OFDMA-based
Homogeneous Cellular Networks (2)

• Game theoretical approach with virtual referee
• This referee mandatorily changes the game rules
  whenever needed, and helps improve the outcome of
  the game.
• Transmit power of UEs with unfavorable channel
  conditions are reduced.
• UEs generating significant interference to others
  may be prohibited from using certain subchannels.
• Low-complexity and heuristic approaches
• Affordable computational complexity
• Reduced feedback overhead
• Suitable for practical applications

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Coordinated Multipoint Transmission and Reception
(CoMP)

• Consider a network with Q cells and K users.
• CoMP allows the data signals to a UE to be sent
  from multiple BSs.
• CoMP utilizes space division multiple access
  (SDMA)
• Each BS can send data signals to multiple
  connected UEs by means of precoding
• Beamformer for UE i at BS q.
• Assuming each UE is assigned to a known subset of
  BSs.

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CoMP for Power Minimization (1)

• Interference Aware (IA)
• Each UE is assigned to only one BS
• BS adjusts its beamformers to ensure a set of
  target SINR at its connected UEs.
• CoMP under IA scheme is a strategic
  noncooperative game.
• Players BSs
• Admissible set of strategies Constraints on the
  SINR at each UE.
• Utility function Transmit power at the BSs
• The beam patterns are always unchanged,
  regardless the ICI power allocation
  game.
• Characterization of the NE existence and
  uniqueness.
• Fully distributed implementation

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CoMP for Power Minimization (2)

• Joint Signal Processing (JP) and Interference
  Coordination (IC)
• Joint optimization to minimize transmit power
  across coordinated BS
• Solution is Pareto-optimal.
• Convex optimization, easy to find the optimal
  solution.
• Multicell problem can be reformulated as a single
  cell problem well-known algorithms can
  be adopted.
• Drawbacks
• Centralized implementation
• Signaling and synchronization between BSs

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CoMP for Power Minimization (3)

• Consider a new game
• Distributed implementation as in IA scheme
• Optimal solution as in IC scheme
• New utility function with pricing
• where pricing factor charged on ICI
  caused by BS q to its unconnected UEs IA
  scheme with pricing
• Under the right pricing scheme, the new game
  approaches optimal performance offered by IC
  scheme.

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CoMP for Power Minimization (4)

• CoMP is more power-efficient than frequency reuse
  scheme.

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CoMP for Rate Maximization (1)

• Interference Aware
• Each UE is assigned to only one BS
• BS adjusts its beamformers to maximize the data
  rate to its connected UEs.
• CoMP under IA scheme is a strategic
  noncooperative game.
• Players BSs
• Admissible set of strategies Power constraint on
  the beamformers
• Utility function Data rate at the BSs
• Nonconcave utility function difficult to
  analyze
• Apply zero-forcing (ZF) at each BS
• Simplify the game into a power iterative
  waterfilling game
• Easier to character of the NE existence and
  uniqueness

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CoMP for Rate Maximization (2)

• Joint Signal Processing (JS) and Interference
  Coordination (IC)
• Joint optimization to maximize the data rate to
  all the UEs
• Nonconvex optimization problem
• Difficult to find global optimum
• Approximation technique to find locally optimal
  solutions
• Solution approaches are usually centralized.
• IA scheme with pricing new utility function with
  pricing
• Under the right pricing, the network sum rate
  monotonically increases to a local maximum.

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CoMP for Rate Maximization (3)

• CoMP extracts higher sum-rate than frequency
  reuse scheme.

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Advanced Interference Coordination Techniques for
CDMA-based Femtocells (1)

• Joint power and admission control for distributed
  interference management with dynamic pricing
  combined with admission control
• Net utility for MUE I to robustly protect the
  performance of all active MUEs
• Update of power for MUE i
• Net utility for FUE j to balance the achieved
  throughput and the power expenditure

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Advanced Interference Coordination Techniques for
CDMA-based Femtocells (2)

• For non-congested network, the proposed algorithm
  quickly converges to an equilibrium with the
  target SINRs achieved for all MUEs.
• For congested network, admission control can
  remove some FUEs, resulting in a noticeable
  growth in SINRs of the remaining FUEs.
• Removal of FUEs does not significantly affect
  the transmit powers and SINRs of MUEs.

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Advanced Interference Coordination Techniques for
CDMA-based Femtocells (3)

• Using convex optimization, distributed joint
  power and SINR allocation is devised such that
• All users attain their respective SINRs that are
  always optimal in Pareto sense,
• Every MUE i is protected with .
• Every FUE j has its utility globally maximized.
• Key steps
• Characterize Pareto-optimal boundary of the SINR
  feasible region
• Use load-spillage parametrization to realize
  every SINR point lying on such a boundary
• Determine a unique operating SINR point, based
  upon the specific network utility function of
  FUEs and the minimum SINR requirements of MUEs,
• Adapt transmit power according to
  Foschini-Miljanic's algorithm to attain such a
  design target.

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Advanced Interference Coordination Techniques for
CDMA-based Femtocells (4)

• Proposed algorithm converges to global optima for
  different utilities.
• Performance of the femtocell network optimized
• Minimum SINRs prescribed for MUEs always
  guaranteed

MUE index 1 2 3 4 5 6 7 8 9 10
Target SINR 1.578 1.507 1.440 1.376 1.315 1.256 1.200 1.147 1.095 1.047
Achieved SINR 1.578 1.507 1.440 1.376 1.315 1.256 1.200 1.147 1.095 1.047
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Advanced Interference Coordination Techniques for
OFDMA-based Femtocells (1)

• Joint allocation of resource block and transmit
  power
• Utility of each femtocell BS includes system
  capacity and other sources of interferences
  (i.e., femtocell to macrocell, macrocell to
  femtocell, and femtocell to femtocell).
• Formulated game belongs to the class of exact
  potential game, shown to always converge to a NE
  when a best response adaptive strategy is
  applied.
• Solution is an iterative process
• Step 1 Optimal resource block allocation is
  determined given a transmit power policy.
• Step 2 Waterfilling allocation of power for
  femtocells is computed for a fixed resource block
  allocation.
• Go back to Step 1 and repeat until convergence.

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Advanced Interference Coordination Techniques for
OFDMA-based Femtocells (2)

• Joint subchannel and transmit power allocation
  scheme
• Femto BSs are allowed to transmit on the same
  subchannel with MUEs as long as interference is
  limited to an acceptable level
• Maximizing capacity of cognitive radio network
  (e.g., femtocell)
• ICI among different cognitive radio cells is
  controlled.
• Lagrangian dual method
• Original design problem is decomposed into
  multiple subproblems in the dual domain
• Each problem is solved by an efficient algorithm.
• Duality gap approaches zero when the number of
  OFDMA subchannels is sufficiently large.
• Proposed solution outperforms the fixed
  subchannel allocation scheme.

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Tradeoff between Spectral and Energy Efficiency

• Spectral Efficiency (SE)
• Energy Efficiency (EE)
• With circuit power Pc

• Tradeoff relation

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Energy-efficient Interference Management for
Multicarrier Multicell Networks

• Given interference power on subchannel k, data
  rate of user i across all subchannels is
• EE of user i
• Given the power allocation of all other users,
  P-i, each user i is required to solve the
  best-response problem
• As is strictly quasiconcave in Pi, there exists
  at least one NE in this power control game.
• Under certain conditions, the NE is unique in
  frequency-selective channels

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Energy-efficient Joint Power Control and
BSAssignment in CDMA-based Multicell Networks

• Utility of user i received at its assigned BS ai
• Two-dimensional space
• Transmit power Pi
• Base station ai
• Power control game with a linear pricing
• Original problem is reduced to
• Improvement in EE with linear pricing is above 25

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Chapter Summary

• Two conflicting goals in cellular network
  deployment spectral v.s energy efficiency
• With universal frequency reuse, new communication
  paradigms are needed to proactively deal with
  intercell interference (ICI).
• Effective coordinating of ICI is the key to
  optimizing the two design goals towards a greener
  cellular network.
• For conventional homogeneous networks, CoMP
  schemes efficiently coordinate or even take
  advantage of the ICI.
• For heterogenous networks, advanced interference
  management mechanisms help mitigate cross-tier
  interference in mixed macrocell/femtocell
  deployment.
• Current advances in ICI coordination improve the
  energy efficiency of cellular networks while
  maintaining a good tradeoff with spectral
  efficiency goal.

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Some Potential Research Directions

• Design CoMP schemes that deal with quantization
  errors, fast-varying channels and CSI feedback
  delay
• Tradeoff between achieving optimal performance
  and incurring low computational complexity in
  CoMP
• Distributed implementation of robust CoMP schemes
  with only local CSI required
• Address energy-efficiency criterion in
  standardization of CoMP techniques
• Determine the optimal cell sizes and locations to
  deploy femtocell BSs, taking into account the
  energy expended for the backhaul and signaling
  overhead
• With cooperative relays, power-efficient resource
  allocation techniques (e.g., energy-efficient
  modulation, selective relaying) should be devised
  and adapted.