diff --git a/inference-engine/src/mkldnn_plugin/nodes/mkldnn_fake_quantize_node.cpp b/inference-engine/src/mkldnn_plugin/nodes/mkldnn_fake_quantize_node.cpp
index 0a5ad38507bda5..b12bed6a47672b 100644
--- a/inference-engine/src/mkldnn_plugin/nodes/mkldnn_fake_quantize_node.cpp
+++ b/inference-engine/src/mkldnn_plugin/nodes/mkldnn_fake_quantize_node.cpp
@@ -10,6 +10,7 @@
 #include <mkldnn_types.h>
 #include <mkldnn_extension_utils.h>
 #include "utils/general_utils.h"
+#include "utils/cpu_utils.hpp"
 
 #include <algorithm>
 #include <set>
@@ -841,7 +842,7 @@ bool MKLDNNFakeQuantizeNode::isSupportedOperation(const std::shared_ptr<const ng
         }
         for (size_t i = 1; i < fq->get_input_size(); i++) {
             size_t count_not_unit_axis = 0;
-            auto shape = fq->get_input_shape(i);
+            auto shape = getNormalizedDimsBySize(fq->get_input_shape(i), fq->get_input_shape(0).size());
 
             if (ngraph::shape_size(shape) != 1) {
                 size_t not_unit_axis = 0;
@@ -885,9 +886,7 @@ MKLDNNFakeQuantizeNode::MKLDNNFakeQuantizeNode(const std::shared_ptr<ngraph::Nod
         if (fq->get_output_size() != 1)
             IE_THROW() << errorPrefix << "has incorrect number of output edges: " << fq->get_output_size();
 
-        auto initAxisIdx = [&](size_t edgeIdx) {
-            const auto &inputDims = fq->get_input_shape(edgeIdx);
-
+        auto initAxisIdx = [&](const ngraph::Shape& inputDims) {
             size_t axisIdx = 0;
             for (int i = 1; i < inputDims.size(); i++) {
                 if (inputDims[i] > 1) {
@@ -898,35 +897,36 @@ MKLDNNFakeQuantizeNode::MKLDNNFakeQuantizeNode(const std::shared_ptr<ngraph::Nod
             return axisIdx;
         };
 
-        axis = fq->get_input_shape(0).size() == 1 ? 0 : 1;
+        const size_t dataNDims = fq->get_input_shape(0).size();
+        axis = dataNDims == 1 ? 0 : 1;
         int axisSize = -1;
 
-        auto inputLowAxis = initAxisIdx(1);
-        const auto ilShape = fq->get_input_shape(1);
+        const auto ilShape = getNormalizedDimsBySize(fq->get_input_shape(1), dataNDims);
+        auto inputLowAxis = initAxisIdx(ilShape);
         isInputLowBroadcasted = (ngraph::is_scalar(ilShape) || ilShape[inputLowAxis] == 1);
         if (!isInputLowBroadcasted) {
             axis = inputLowAxis;
             axisSize = ilShape[inputLowAxis];
         }
 
-        auto inputHighAxis = initAxisIdx(2);
-        const auto ihShape = fq->get_input_shape(2);
+        const auto ihShape = getNormalizedDimsBySize(fq->get_input_shape(2), dataNDims);
+        auto inputHighAxis = initAxisIdx(ihShape);
         isInputHighBroadcasted = (ngraph::is_scalar(ihShape) || ihShape[inputHighAxis] == 1);
         if (!isInputHighBroadcasted) {
             axis = inputHighAxis;
             axisSize = ihShape[inputHighAxis];
         }
 
-        auto outputLowAxis = initAxisIdx(3);
-        const auto olShape = fq->get_input_shape(3);
+        const auto olShape = getNormalizedDimsBySize(fq->get_input_shape(3), dataNDims);
+        auto outputLowAxis = initAxisIdx(olShape);
         isOutputLowBroadcasted = (ngraph::is_scalar(olShape) || olShape[outputLowAxis] == 1);
         if (!isOutputLowBroadcasted) {
             axis = outputLowAxis;
             axisSize = olShape[outputLowAxis];
         }
 
-        auto outputHighAxis = initAxisIdx(4);
-        const auto ohShape = fq->get_input_shape(4);
+        const auto ohShape = getNormalizedDimsBySize(fq->get_input_shape(4), dataNDims);
+        auto outputHighAxis = initAxisIdx(ohShape);
         isOutputHighBroadcasted = (ngraph::is_scalar(ohShape) || ohShape[outputHighAxis] == 1);
         if (!isOutputHighBroadcasted) {
             axis = outputHighAxis;
diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/fake_quantize.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/fake_quantize.cpp
index fcaa41f72f09d3..3dbb6f5fd539b5 100644
--- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/fake_quantize.cpp
+++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/fake_quantize.cpp
@@ -89,4 +89,27 @@ INSTANTIATE_TEST_CASE_P(smoke_FakeQuantizePerChannelAxis1, FakeQuantizeLayerTest
                                 ::testing::Values(CommonTestUtils::DEVICE_CPU),
                                 ::testing::Values(config)),
                         FakeQuantizeLayerTest::getTestCaseName);
+
+const std::vector<std::vector<size_t>> inputShapesPerChannel2D = {{1, 10}};
+const std::vector<std::vector<size_t>> constShapesPerChannel2D = { {10}, {1, 10}, {1} };
+const auto fqParamsPerChannel2D = ::testing::Combine(
+    ::testing::ValuesIn(levels),
+    ::testing::ValuesIn(constShapesPerChannel2D),
+    ::testing::Values(fqArgs),
+    ::testing::Values(inputParams)
+);
+
+INSTANTIATE_TEST_CASE_P(smoke_FakeQuantizePerChannel2D, FakeQuantizeLayerTest,
+    ::testing::Combine(
+        fqParamsPerChannel2D,
+        ::testing::ValuesIn(netPrecisions),
+        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(inputShapesPerChannel2D),
+        ::testing::Values(CommonTestUtils::DEVICE_CPU),
+        ::testing::Values(config)),
+    FakeQuantizeLayerTest::getTestCaseName);
+
 }  // namespace